Quantitative assessment of liver fibrosis reveals a nonlinear association with fibrosis stage in nonalcoholic fatty liver disease

Chronological changes in etiology, pathological and imaging findings in primary liver cancer from 2001 to 2020

PURPOSE

To achieve a historical perspective, the chronological changes in primary liver cancer over a 20-year period were investigated at a single institution, focusing on shifts in etiology and the impact on imaging and pathological findings using The Liver Imaging Reporting and Data System.

MATERIALS AND METHODS

A retrospective study of surgically resected primary liver cancer in 680 patients from 2001 to 2020 resulted in 434 patients with 482 nodules being analyzed. Dynamic contrast-enhanced computed tomography imaging and the Liver Imaging Reporting and Data System 2018 classification were employed. Two pathologists and two radiologists independently evaluated specimens and images.

RESULTS

This study highlighted a significant decline in cases of viral hepatitis and cirrhosis in primary liver cancer patients but an increase in intrahepatic cholangiocarcinoma and scirrhous hepatocellular carcinoma. Notably, there was a rise in non-viral hepatitis cases, potentially pointing toward an increase in steatohepatitic hepatocellular carcinoma cases in the future. Intrahepatic cholangiocarcinoma, scirrhous hepatocellular carcinoma and steatohepatitic hepatocellular carcinoma tumors exhibited slightly different distributions in the Liver Imaging Reporting and Data System classification compared with ordinary hepatocellular carcinoma, which may reflect the presence of fibrosis and lipid in tumor parenchyma.

CONCLUSIONS

Consistent with past reports, this study demonstrated the emergence of primary liver cancer against a backdrop of non-viral and non-cirrhotic liver. Liver Imaging Reporting and Data System has been consistently useful in diagnosing primary liver cancer; however, among the histological subtypes of hepatocellular carcinoma, an increase is anticipated in scirrhous hepatocellular carcinoma and steatohepatitic hepatocellular carcinoma, which may present imaging findings different from those of ordinary hepatocellular carcinoma. This development may necessitate a reevaluation of the current approach for diagnosing and treating hepatocellular carcinoma based solely on imaging.

Digital Pathology Tailored for Assessment of Liver Biopsies

Improved image quality, better scanners, innovative software technologies, enhanced computational power, superior network connectivity, and the ease of virtual image reproduction and distribution are driving the potential use of digital pathology for diagnosis and education. Although relatively common in clinical oncology, its application in liver pathology is under development. Digital pathology and improving subjective histologic scoring systems could be essential in managing obesity-associated steatotic liver disease. The increasing use of digital pathology in analyzing liver specimens is particularly intriguing as it may offer a more detailed view of liver biology and eliminate the incomplete measurement of treatment responses in clinical trials. The objective and automated quantification of histological results may help establish standardized diagnosis, treatment, and assessment protocols, providing a foundation for personalized patient care. Our experience with artificial intelligence (AI)-based software enhances reproducibility and accuracy, enabling continuous scoring and detecting subtle changes that indicate disease progression or regression. Ongoing validation highlights the need for collaboration between pathologists and AI developers. Concurrently, automated image analysis can address issues related to the historical failure of clinical trials stemming from challenges in histologic assessment. We discuss how these novel tools can be incorporated into liver research and complement post-diagnosis scenarios where quantification is necessary, thus clarifying the evolving role of digital pathology in the field.

Influence of dispersion slope on the diagnosis of liver fibrosis by the shear wave in metabolic dysfunction-associated steatotic liver disease

AIM

Shear wave (SW) elastography is used to evaluate metabolic dysfunction-associated steatotic liver disease (MASLD) pathophysiology. Increased elasticity due to fibrosis and increased viscosity due to necrosis and inflammation affect SW. Assessing fibrosis, the most prognostically relevant pathology, is critical. Viscosity is evaluated using the dispersion slope (DS); however, cut-off values that affect SW values are unclear. We compared the ultrasound imaging parameters (SW for viscoelasticity; DS for viscosity) with pathological findings.

METHODS

Patients (n = 159) who underwent liver biopsy and SW and DS assessments at our hospital were included. Fibrosis stage and inflammation grade cut-off values were calculated from SW, DS, and liver biopsy results using receiver operating characteristic curves. Cases in which liver biopsy results were inconsistent with SW results were used to determine the effect of viscosity on SW values. DS was examined in the Correct and Incorrect Diagnosis groups, which were categorized based on the concordance between SW and liver biopsy results. Dispersion slope cut-off values between the two groups were calculated.

RESULTS

Fibrosis stage cut-off values by SW (m/s) were: ≥F2, 1.62; ≥F3, 1.74; and F4, 1.97. Inflammation grade cut-off values by DS (m/s/kHz) were: ≥A1, 11.6; ≥A2, 14.5; and A3, 16.1. The Correct/Incorrect Diagnosis groups had 25/70 patients. The DS cut-off value for both groups was 13.2 m/s/kHz.

CONCLUSIONS

Shear wave and DS are useful for evaluating liver fibrosis and inflammation in MASLD. For DS > 13.2 m/s/kHz, SW may be affected by the increased viscosity owing to inflammation. In such patients, caution should be used when determining/interpreting values.

Liver fibrosis analysis using digital pathology

Digital pathology has enabled the noninvasive quantification of pathological parameters. In addition, the combination of digital pathology and artificial intelligence has enabled the analysis of a vast amount of information, leading to the sharing of much information and the elimination of knowledge gaps. Fibrosis, which reflects chronic inflammation, is the most important pathological parameter in chronic liver diseases, such as viral hepatitis and metabolic dysfunction-associated steatotic liver disease. It has been reported that the quantitative evaluation of various fibrotic parameters by digital pathology can predict the prognosis of liver disease and hepatocarcinogenesis. Liver fibrosis evaluation methods include 1 fiber quantification, 2 elastin and collagen quantification, 3 s harmonic generation/two photon excitation fluorescence (SHG/TPE) microscopy, and 4 Fibronest™..　In this review, we provide an overview of role of digital pathology on the evaluation of fibrosis in liver disease and the characteristics of recent methods to assess liver fibrosis.

Clinical Application of Quantitative MR Imaging in Nonalcoholic Fatty Liver Disease

Viral hepatitis was previously the most common cause of chronic liver disease. However, in recent years, nonalcoholic fatty liver disease (NAFLD) cases have been increasing, especially in developed countries. NAFLD is histologically characterized by fat, fibrosis, and inflammation in the liver, eventually leading to cirrhosis and hepatocellular carcinoma. Although biopsy is the gold standard for the assessment of the liver parenchyma, quantitative evaluation methods, such as ultrasound, CT, and MRI, have been reported to have good diagnostic performances. The quantification of liver fat, fibrosis, and inflammation is expected to be clinically useful in terms of the prognosis, early intervention, and treatment response for the management of NAFLD. The aim of this review was to discuss the basics and prospects of MRI-based tissue quantifications of the liver, mainly focusing on proton density fat fraction for the quantification of fat deposition, MR elastography for the quantification of fibrosis, and multifrequency MR elastography for the evaluation of inflammation.

Sample size calculation for a NanoString GeoMx spatial transcriptomics experiment to study predictors of fibrosis progression in non-alcoholic fatty liver disease

Sample size calculation for spatial transcriptomics is a novel and understudied research topic. Prior publications focused on powering spatial transcriptomics studies to detect specific cell populations or spatially variable expression patterns on tissue slides. However, power calculations for translational or clinical studies often relate to the difference between patient groups, and this is poorly described in the literature. Here, we present a stepwise process for sample size calculation to identify predictors of fibrosis progression in non-alcoholic fatty liver disease as a case study. We illustrate how to infer study hypothesis from prior bulk RNA-sequencing data, gather input requirements and perform a simulation study to estimate required sample size to evaluate gene expression differences between patients with stable fibrosis and fibrosis progressors with NanoString GeoMx Whole Transcriptome Atlas assay.

Construction of an RNA modification-related gene predictive model associated with prognosis and immunity in gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most common causes of cancer-related fatalities worldwide, and its progression is associated with RNA modifications. Here, using RNA modification-related genes (RNAMRGs), we aimed to construct a prognostic model for patients with GC.

METHODS

Based on RNAMRGs, RNA modification scores (RNAMSs) were obtained for GC samples from The Cancer Genome Atlas and were divided into high- and low-RNAMS groups. Differential analysis and weighted correlation network analysis were performed for the differential expressed genes (DEGs) to obtain the key genes. Next, univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses were performed to obtain the model. According to the model risk score, samples were divided into high- and low-risk groups. Enrichment analysis and immunoassays were performed for the DEGs in these groups. Four external datasets from Gene Expression Omnibus data base were used to test the accuracy of the predictive model.

RESULTS

We identified SELP and CST2 as key DEGs, which were used to generate the predictive model. The high-risk group had a worse prognosis compared to the low-risk group (p < 0.05). Enrichment analysis and immunoassays revealed that 144 DEGs related to immune cell infiltration were associated with the Wnt signaling pathway and included hub genes such as ELN. Overall mutation levels, tumor mutation burden, and microsatellite instability were lower, but tumor immune dysfunction and exclusion scores were greater (p < 0.05) in the high-risk group than in the low-risk group. The validation results showed that the prediction model score can accurately predict the prognosis of GC patients. Finally, a nomogram was constructed using the risk score combined with the clinicopathological characteristics of patients with GC.

CONCLUSION

This risk score from the prediction model related to the tumor microenvironment and immunotherapy could accurately predict the overall survival of GC patients.

Multiparametric Tissue Characterization Utilizing the Cellular Metallome and Immuno-Mass Spectrometry Imaging

In this study, we present a workflow that enables spatial single-cell metallomics in tissue decoding the cellular heterogeneity. Low-dispersion laser ablation in combination with inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOFMS) provides mapping of endogenous elements with cellular resolution at unprecedented speed. Capturing the heterogeneity of the cellular population by metals only is of limited use as the cell type, functionality, and cell state remain elusive. Therefore, we expanded the toolbox of single-cell metallomics by integrating the concepts of imaging mass cytometry (IMC). This multiparametric assay successfully utilizes metal-labeled antibodies for cellular tissue profiling. One important challenge is the need to preserve the original metallome in the sample upon immunostaining. Therefore, we studied the impact of extensive labeling on the obtained endogenous cellular ionome data by quantifying elemental levels in consecutive tissue sections (with and without immunostaining) and correlating elements with structural markers and histological features. Our experiments showed that the elemental tissue distribution remained intact for selected elements such as sodium, phosphorus, and iron, while absolute quantification was precluded. We hypothesize that this integrated assay not only advances single-cell metallomics (enabling to link metal accumulation to multi-dimensional characterization of cells/cell populations), but in turn also enhances selectivity in IMC, as in selected cases, labeling strategies can be validated by elemental data. We showcase the power of this integrated single-cell toolbox using an in vivo tumor model in mice and provide mapping of the sodium and iron homeostasis as linked to different cell types and function in mouse organs (such as spleen, kidney, and liver). Phosphorus distribution maps added structural information, paralleled by the DNA intercalator visualizing the cellular nuclei. Overall, iron imaging was the most relevant addition to IMC. In tumor samples, for example, iron-rich regions correlated with high proliferation and/or located blood vessels, which are key for potential drug delivery.

Surveillance of the progression and assessment of treatment endpoints for nonalcoholic steatohepatitis

Nonalcoholic steatohepatitis (NASH) is an aggressive form of nonalcoholic fatty liver disease (NAFLD) characterized by steatosis-associated inflammation and liver injury. Without effective treatment or management, NASH can have life-threatening outcomes. Evaluation and identification of NASH patients at risk for adverse outcomes are therefore important. Key issues in screening NASH patients are the assessment of advanced fibrosis, differentiation of NASH from simple steatosis, and monitoring of dynamic changes during follow-up and treatment. Currently, NASH staging and evaluation of the effectiveness for drugs still rely on pathological diagnosis, despite sample error issues and the subjectivity associated with liver biopsy. Optimizing the pathological assessment of liver biopsy samples and developing noninvasive surrogate methods for accessible, accurate, and safe evaluation are therefore critical. Although noninvasive methods including elastography, serum soluble biomarkers, and combined models have been implemented in the last decade, noninvasive diagnostic measurements are not widely applied in clinical practice. More work remains to be done in establishing cost-effective strategies both for screening for at-risk NASH patients and identifying changes in disease severity. In this review, we summarize the current state of noninvasive methods for detecting steatosis, steatohepatitis, and fibrosis in patients with NASH, and discuss noninvasive assessments for screening at-risk patients with a focus on the characteristics that should be monitored at follow-up.

Application of digital pathology and machine learning in the liver, kidney and lung diseases

The development of rapid and accurate Whole Slide Imaging (WSI) has paved the way for the application of Artificial Intelligence (AI) to digital pathology. The availability of WSI in the recent years allowed the rapid development of various AI technologies to blossom. WSI-based digital pathology combined with neural networks can automate arduous and time-consuming tasks of slide evaluation. Machine Learning (ML)-based AI has been demonstrated to outperform pathologists by eliminating inter- and intra-observer subjectivity, obtaining quantitative data from slide images, and extracting hidden image patterns that are relevant to disease subtype and progression. In this review, we outline the functionality of different AI technologies such as neural networks and deep learning and discover how aspects of different diseases make them benefit from the implementation of AI. AI has proven to be valuable in many different organs, with this review focusing on the liver, kidney, and lungs. We also discuss how AI and image analysis not only can grade diseases objectively but also discover aspects of diseases that have prognostic value. In the end, we review the current status of the integration of AI in pathology and share our vision on the future of digital pathology.

A 3-step approach to predict advanced fibrosis in nonalcoholic fatty liver disease: impact on diagnosis, patient burden, and medical costs

A 2-step approach, Fibrosis-4 index (FIB-4) followed by vibration-controlled transient elastography (VCTE), has been proposed to predict advanced fibrosis in patients with nonalcoholic fatty liver disease (NAFLD). We aimed to develop a novel 3-step approach for predicting advanced fibrosis. We enrolled 284 biopsy-confirmed NAFLD patients from two tertiary care centers and developed subgroups (n = 190), including 3.7% of patients with advanced fibrosis, assuming a primary care setting. In the 3-step approach, patients with intermediate-to-high FIB-4 in the first step underwent an enhanced liver fibrosis test or measurement of type IV collagen 7S domain as the second step, and VCTE was performed if the second step value was higher than the cutoff. In 284 cases, a tertiary care cohort with 36.3% advanced fibrosis, the 3-step approach showed significantly higher specificity and positive predictive value than the 2-step approach. In the subgroup with 3.7% advanced fibrosis, the 3-step approach significantly reduced the referral rate to specialists, the number of high-risk patients (i.e., liver biopsy candidates), and healthcare costs by 12.5% to 15.8%. The 3-step approach may improve the diagnostic performance to predict advanced fibrosis in NAFLD, which could lower rates of referrals to specialists, liver biopsies, and medical costs.

Liver fibrosis assessment: MR and US elastography

Elastography has emerged as a preferred non-invasive imaging technique for the clinical assessment of liver fibrosis. Elastography methods provide liver stiffness measurement (LSM) as a surrogate quantitative biomarker for fibrosis burden in chronic liver disease (CLD). Elastography can be performed either with ultrasound or MRI. Currently available ultrasound-based methods include strain elastography, two-dimensional shear wave elastography (2D-SWE), point shear wave elastography (pSWE), and vibration-controlled transient elastography (VCTE). MR Elastography (MRE) is widely available as two-dimensional gradient echo MRE (2D-GRE-MRE) technique. US-based methods provide estimated Young's modulus (eYM) and MRE provides magnitude of the complex shear modulus. MRE and ultrasound methods have proven to be accurate methods for detection of advanced liver fibrosis and cirrhosis. Other clinical applications of elastography include liver decompensation prediction, and differentiation of non-alcoholic steatohepatitis (NASH) from simple steatosis (SS). In this review, we briefly describe the different elastography methods, discuss current clinical applications, and provide an overview of advances in the field of liver elastography.

A randomized, double-blind, placebo-controlled phase IIa trial of efruxifermin for patients with compensated NASH cirrhosis

Background & Aims

Efruxifermin has shown clinical efficacy in patients with non-alcoholic steatohepatitis (NASH) and F1-F3 fibrosis. The primary objective of the BALANCED Cohort C was to assess the safety and tolerability of efruxifermin in patients with compensated NASH cirrhosis.

Methods

Patients with NASH and stage 4 fibrosis (n = 30) were randomized 2:1 to receive efruxifermin 50 mg (n = 20) or placebo (n = 10) once-weekly for 16 weeks. The primary endpoint was safety and tolerability of efruxifermin. Secondary and exploratory endpoints included evaluation of non-invasive markers of liver injury and fibrosis, glucose and lipid metabolism, and changes in histology in a subset of patients who consented to end-of-study liver biopsy.

Results

Efruxifermin was safe and well-tolerated; most adverse events (AEs) were grade 1 (n = 7, 23.3%) or grade 2 (n = 19, 63.3%). The most frequent AEs were gastrointestinal, including transient, mild to moderate diarrhea, and/or nausea. Significant improvements were noted in key markers of liver injury (alanine aminotransferase) and glucose and lipid metabolism. Sixteen-week treatment with efruxifermin was associated with significant reductions in non-invasive markers of fibrosis including Pro-C3 (least squares mean change from baseline [LSMCFB] -9 μg/L efruxifermin vs. -3.4 μg/L placebo; p = 0.0130) and ELF score (-0.4 efruxifermin vs. +0.4 placebo; p = 0.0036), with a trend towards reduced liver stiffness (LSMCFB -5.7 kPa efruxifermin vs. -1.1 kPa placebo; n.s.). Of 12 efruxifermin-treated patients with liver biopsy after 16 weeks, 4 (33%) achieved fibrosis improvement of at least one stage without worsening of NASH, while an additional 3 (25%) achieved resolution of NASH, compared to 0 of 5 placebo-treated patients.

Conclusions

Efruxifermin appeared safe and well-tolerated with encouraging improvements in markers of liver injury, fibrosis, and glucose and lipid metabolism following 16 weeks of treatment, warranting confirmation in larger and longer term studies.

Lay summary

Cirrhosis resulting from non-alcoholic steatohepatitis (NASH), the progressive form of non-alcoholic fatty liver disease, represents a major unmet medical need. Currently there are no approved drugs for the treatment of NASH. This proof-of-concept randomized, double-blind clinical trial demonstrated the potential therapeutic benefit of efruxifermin treatment compared to placebo in patients with cirrhosis due to NASH.

Clinical Trial Number

NCT03976401.

Fibrosis regression following hepatitis C antiviral therapy

Hepatitis C virus (HCV) infection is one of the most common causes of liver pathology. It is a major etiological factor of continuous liver injury by triggering an uncontrolled inflammatory response, causing liver fibrosis and cirrhosis. Liver fibrosis is a dynamic process that can be reversible upon timely cessation of the injurious agent, which in cases of HCV is represented by the sustained virological response (SVR) following antiviral therapies. Direct-acting antiviral therapy has recently revolutionized HCV therapy and minimized complications. Liver fibrosis can be assessed with variable invasive and non-invasive methods, with certain limitations. Despite the broad validation of the diagnostic and prognostic value of non-invasive modalities of assessment of liver fibrosis in patients with HCV, the proper interpretation of liver stiffness measurement in patients after SVR remains unclear. It is also still a debate whether this regression is caused by the resolution of liver injury following treatment of HCV, rather than true fibrosis regression. Regression of liver fibrosis can possess a positive impact on patient's quality of life reducing the incidence of complications. However, fibrosis regression does not abolish the risk of developing hepatocellular carcinoma, which mandates regular screening of patients with advanced fibrosis.

Current status and challenges in the drug treatment for fibrotic nonalcoholic steatohepatitis

Currently, nonalcoholic steatohepatitis (NASH) is one of the most common forms of chronic hepatitis, increasing the burden of health care worldwide. In patients with NASH, the fibrosis stage is the most predictive factor of long-term events. However, there are still no drugs approved by the Food and Drug Administration of the United States for treating biopsy-proven NASH with fibrosis or cirrhosis. Although some novel drugs have shown promise in preclinical studies and led to improvement in terms of hepatic fat content and steatohepatitis, a considerable proportion of them have failed to achieve histological endpoints of fibrosis improvement. Due to the large number of NASH patients and adverse clinical outcomes, the search for novel drugs is necessary. In this review, we discuss current definitions for the evaluation of treatment efficacy in fibrosis improvement for NASH patients, and we summarize novel agents in the pipeline from different mechanisms and phases of trial. We also critically review the challenges we face in the development of novel agents for fibrotic NASH and NASH cirrhosis.

Liver fibrosis quantification

Liver fibrosis (LF) is the wound healing response to chronic liver injury. LF is the endpoint of chronic liver disease (CLD) regardless of etiology and the single most important determinant of long-term liver-related clinical outcomes. Quantification of LF is important for staging, to evaluate response to treatment and to predict outcomes. LF is traditionally staged by liver biopsy. However, liver biopsy is invasive and suffers from sampling errors when biopsy size is inadequate; therefore, non-invasive tests (NITs) have found important roles in clinical care. NITs include simple laboratory-based serum tests, panels of serum tests, and imaging biomarkers. NITs are validated against the liver biopsy and will be used in the future for evaluation of nearly all CLDs with invasive liver biopsy reserved for some cases. Both serum tests and some imaging biomarkers such as elastography are currently used clinically as surrogate markers for LF. Several other imaging biomarkers are still considered research and awaiting clinical application in the future. As the evaluation of imaging biomarkers will likely become the norm in the future, understanding pathogenesis of LF is important. Knowledge of properties measured by imaging biomarkers and its correlation with LF is important to understand the application of NITs by abdominal radiologists. In this review, we present a brief overview of pathogenesis of LF, spatiotemporal evolution of LF in different CLD, and severity assessment with liver biopsy. This will be followed by a brief discussion on properties measured by imaging biomarkers and their relationship to the LF.

Impact of qualitative endoscopic ultrasonography on fatty pancreas at a referral medical center

Background

Taking advantage of the current advances in diagnostic imaging modalities, including endoscopic ultrasonography (EUS), and due to the increased attention to ectopic fat accumulation in the pancreas following the rising trend of metabolic syndrome, we qualitatively assessed the clinical implication of pancreatic steatosis by EUS in this study.

Methods

The study included 243 patients that were divided into four groups. The correlation between the average echogenicity of the pancreas and that of the control organs and the key clinical data of all study patients were collectively analyzed. The cut‐off point of the pancreas‐control (PC) ratio in EUS and liver‐control (LC) ratio on abdominal ultrasound were determined from the population distribution and the obtained median values.

Results

With the cut‐off point of 1.30 for the PC ratio and 1.20 for the LC ratio, sex, the Brinkman index, habitual alcohol drinkers, and fatty pancreas were significant factors. The associations between each relevant factor in fatty pancreas, metabolic syndrome in the fatty liver group, and age in the pancreatic cancer group were all significant in the analysis. In addition, we investigated whether the PC ratio differed according to age and staging in pancreatic cancer patients. Interestingly, the PC ratio was lower in the advanced stage group than in the early‐stage group.

Conclusion

Our results suggest that, irrespective of the degree, ectopic fat infiltration in the pancreas could be a specific clinical phenotype of serious pancreatic diseases, including pancreatic cancer, especially in high‐risk patients.

Digital Pathology Enables Automated and Quantitative Assessment of Inflammatory Activity in Patients with Chronic Liver Disease

Traditional histological evaluation for grading liver disease severity is based on subjective and semi-quantitative scores. We examined the relationship between digital pathology analysis and corresponding scoring systems for the assessment of hepatic necroinflammatory activity. A prospective, multicenter study including 156 patients with chronic liver disease (74% nonalcoholic fatty liver disease-NAFLD, 26% chronic hepatitis-CH etiologies) was performed. Inflammation was graded according to the Nonalcoholic Steatohepatitis (NASH) Clinical Research Network system and METAVIR score. Whole-slide digital image analysis based on quantitative (I-score: inflammation ratio) and morphometric (C-score: proportionate area of staining intensities clusters) measurements were independently performed. Our data show that I-scores and C-scores increase with inflammation grades (p < 0.001). High correlation was seen for CH (ρ = 0.85-0.88), but only moderate for NAFLD (ρ = 0.5-0.53). I-score (p = 0.008) and C-score (p = 0.002) were higher for CH than NAFLD. Our MATLAB algorithm performed better than QuPath software for the diagnosis of low-moderate inflammation (p < 0.05). C-score AUC for classifying NASH was 0.75 (95%CI, 0.65-0.84) and for moderate/severe CH was 0.99 (95%CI, 0.97-1.00). Digital pathology measurements increased with fibrosis stages (p < 0.001). In conclusion, quantitative and morphometric metrics of inflammatory burden obtained by digital pathology correlate well with pathologists' scores, showing a higher accuracy for the evaluation of CH than NAFLD.

Evaluation of HCV-related liver fibrosis post-successful DAA therapy

Background

The rapidly developing era of direct-acting antiviral regimens (DAAs) for more than one hepatitis C virus (HCV) genotype had certainly alleviated HCV burden all over the world. Liver fibrosis is the major dramatic complication of HCV infection, and its progression leads to cirrhosis, liver failure, and hepatocellular carcinoma. The impact of DAAs on liver fibrosis had been debatably evaluated with undetermined resolution.

Main body

The aim of this review is to accurately revise the effects of DAA regimens on liver fibrosis which can either be regression, progression, or non-significant association. Liver fibrosis regression is a genuine fact assured by many retrospective and prospective clinical studies. Evaluation could be concluded early post-therapy reflecting the dynamic nature of the process.

Conclusions

The ideal application of DAA regimens in treating HCV has to be accomplished with efficient non-invasive markers in differentiating proper fibrosis evaluation from necroinflammation consequences. Liver biopsy is the gold standard that visualizes the dynamic of fibrosis regression.

SOFTWARE-ASSISTED IMAGE ANALYSIS FOR IDENTIFICATION AND QUANTIFICATION OF HEPATIC SINUSOIDAL DILATATION AND CENTRILOBULAR FIBROSIS

Background:

Heart dysfunction and liver disease often coexist because of systemic disorders. Any cause of right ventricular failure may precipitate hepatic congestion and fibrosis. Digital image technologies have been introduced to pathology diagnosis, allowing an objective quantitative assessment. The quantification of fibrous tissue in liver biopsy sections is extremely important in the classification, diagnosis and grading of chronic liver disease.

Aim:

To create a semi-automatic computerized protocol to quantify any amount of centrilobular fibrosis and sinusoidal dilatation in liver Masson’s Trichrome-stained specimen.

Method:

Once fibrosis had been established, liver samples were collected, histologically processed, stained with Masson’s trichrome, and whole-slide images were captured with an appropriated digital pathology slide scanner. After, a random selection of the regions of interest (ROI’s) was conducted. The data were subjected to software-assisted image analysis (ImageJ^®).

Results:

The analysis of 250 ROI’s allowed to empirically obtain the best application settings to identify the centrilobular fibrosis (CF) and sinusoidal lumen (SL). After the establishment of the colour threshold application settings, an in-house Macro was recorded to set the measurements (fraction area and total area) and calculate the CF and SL ratios by an automatic batch processing.

Conclusion:

Was possible to create a more detailed method that identifies and quantifies the area occupied by fibrous tissue and sinusoidal lumen in Masson’s trichrome-stained livers specimens.

Artificial Intelligence in Imaging of Chronic Liver Diseases: Current Update and Future Perspectives

Here we review artificial intelligence (AI) models which aim to assess various aspects of chronic liver disease. Despite the clinical importance of hepatocellular carcinoma in the setting of chronic liver disease, we focus this review on AI models which are not lesion-specific and instead review models developed for liver parenchyma segmentation, evaluation of portal circulation, assessment of hepatic fibrosis, and identification of hepatic steatosis. Optimization of these models offers the opportunity to potentially reduce the need for invasive procedures such as catheterization to measure hepatic venous pressure gradient or biopsy to assess fibrosis and steatosis. We compare the performance of these AI models amongst themselves as well as to radiomics approaches and alternate modality assessments. We conclude that these models show promising performance and merit larger-scale evaluation. We review artificial intelligence models that aim to assess various aspects of chronic liver disease aside from hepatocellular carcinoma. We focus this review on models for liver parenchyma segmentation, evaluation of portal circulation, assessment of hepatic fibrosis, and identification of hepatic steatosis. We conclude that these models show promising performance and merit a larger scale evaluation.

Elastic Fibers Density: a New Parameter of Improvement of NAFLD in Bariatric Surgery Patients

PURPOSE

Obesity is a major risk factor for nonalcoholic fatty liver disease (NAFLD), affecting 25% of the worldwide population. Weight loss through bariatric surgery can improve much of the liver steatosis, inflammation, and fibrosis. However, it is not known whether there is reversal of the elastic fiber deposition process, triggered by hepatic damage and related to worse prognosis.

MATERIALS AND METHODS

Individuals submitted to bariatric surgery at our institution, from March 2016 to June 2017, with intraoperative liver biopsy confirming NAFLD were approached. Those who consented were submitted to a second liver biopsy 1 year later and were included. Specimens were sliced and stained with hematoxylin-eosin and Sirius red for histological assessment according to Brunt's criteria and with orcein for digital analysis morphometrics using ImageJ®. Quantification of elastic fibers was accomplished by corrected integrated density.

RESULTS

Thirty-seven patients were included. Body mass index, metabolic markers, NAFLD activity score, and fibrosis improved 1 year after the procedure. The elastic fiber density showed a significant decrease: 239.3 × 10³ absorbance micrometer² (141.08-645.32) to 74.62 × 10³ absorbance micrometer² (57.42-145.17), p = 0.007.

CONCLUSION

Liver elastic fiber density decreases with the reversal of NAFLD through weight loss.

Digital pathology: accurate technique for quantitative assessment of histological features in metabolic-associated fatty liver disease

BACKGROUND

Histological evaluation of metabolic-associated fatty liver disease (MAFLD) biopsies is subjective, descriptive and with interobserver variability.

AIMS

To examine the relationship between different histological features (fibrosis, steatosis, inflammation and iron) measured with automated whole-slide quantitative digital pathology and corresponding semiquantitative scoring systems, and the distribution of digital pathology measurements across Fatty Liver Inhibition of Progression (FLIP) algorithm and Steatosis, Activity and Fibrosis (SAF) scoring system METHODS: We prospectively included 136 consecutive patients who underwent liver biopsy for MAFLD at three Spanish centres (January 2017-January 2020). Biopsies were scored by two blinded pathologists according to the Non-alcoholic Steatohepatitis (NASH) Clinical Research Network system for fibrosis staging, the FLIP/SAF classification for steatosis and inflammation grading and Deugnier score for iron grading. Proportionate areas of collagen, fat, inflammatory cells and iron deposits were measured with computer-assisted digital image analysis. A test-retest experiment was performed for precision repeatability evaluation.

RESULTS

Digital pathology showed strong correlation with fibrosis (r = 0.79; P < 0.001), steatosis (r = 0.85; P < 0.001) and iron (r = 0.70; P < 0.001). Performance was lower when assessing the degree of inflammation (r = 0.35; P < 0.001). NASH cases had a higher proportion of collagen and fat compared to non-NASH cases (P < 0.005), whereas inflammation and iron quantification did not show significant differences between categories. Repeatability evaluation showed that all the coefficients of variation were ≤1.1% and all intraclass correlation coefficient values were ≥0.99, except those of collagen.

CONCLUSION

Digital pathology allows an automated, precise, objective and quantitative assessment of MAFLD histological features. Digital analysis measurements show good concordance with pathologists´ scores.

Liver biopsy in the quantitative assessment of liver fibrosis in nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease/nonalcoholic steatohepatitis (NAFLD/NASH) is a major cause of liver fibrosis/cirrhosis and liver-related mortality. Despite emergence of noninvasive tests, liver biopsy remains the mainstay for the diagnosis and assessment of disease severity and chronicity. Accurate detection and quantification of liver fibrosis with architectural localization are essential for assessing the severity of NAFLD and its response to antifibrotic therapy in clinical trials. Conventional histological scoring systems for liver fibrosis are semiquantitative. Collagen proportionate area is morphometric by measuring the percentage of fibrosis on a continuous scale but is limited by the absence of architectural input. Ultra-fast laser microscopy, e.g., second harmonic generation (SHG) imaging, has enabled in-depth analysis of fibrillary collagen based on intrinsic optical signals. Quantification and calculation of different detailed variables of collagen fibers can be used to establish algorithm-based quantitative fibrosis scores (e.g. qFibrosis, q-FPs) in NAFLD. Artificial intelligence is being explored to further develop quantitative fibrosis scoring methods. SHG microscopy should be considered the new gold standard for the quantitative assessment of liver fibrosis, reaffirming the pivotal role of the liver biopsy in NAFLD, at least for the near-future. The ability of SHG-derived algorithms to intuitively detect subtle nuances in liver fibrosis changes over a continuous scale should be employed to redress the efficacy endpoint for fibrosis in NASH clinical trials. The current decrease by 1-point or more in fibrosis stage may not be realistic for the evaluation of therapeutic response to antifibrotic drugs in relatively short-term trials.

Updates in the quantitative assessment of liver fibrosis for nonalcoholic fatty liver disease: Histological perspective

Nonalcoholic fatty liver disease/nonalcoholic steatohepatitis (NAFLD/NASH) is a major cause of liver fibrosis and cirrhosis. Accurate assessment of liver fibrosis is important for predicting disease outcomes and assessing therapeutic response in clinical practice and clinical trials. Although noninvasive tests such as transient elastography and magnetic resonance elastography are preferred where possible, histological assessment of liver fibrosis via semiquantitative scoring systems remains the current gold standard. Collagen proportionate area provides more granularity by measuring the percentage of fibrosis on a continuous scale, but is limited by the absence of architectural input. Although not yet used in routine clinical practice, advances in second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy imaging show great promise in characterising architectural features of fibrosis at the individual collagen fiber level. Quantification and calculation of different detailed variables of collagen fibers can be used to establish algorithm-based quantitative fibrosis scores (e.g., qFibrosis, q-FPs), which have been validated against fibrosis stage in NAFLD. Artificial intelligence is being explored to further refine and develop quantitative fibrosis scoring methods. SHG-microscopy shows promise as the new gold standard for the quantitative measurement of liver fibrosis. This has reaffirmed the pivotal role of the liver biopsy in fibrosis assessment in NAFLD, at least for the near-future. The ability of SHG-derived algorithms to intuitively detect subtle nuances in liver fibrosis changes over a continuous scale should be employed to redress the efficacy endpoint for fibrosis in NASH clinical trials; this approach may improve the outcomes of the trials evaluating therapeutic response to antifibrotic drugs.

MR elastography of liver: current status and future perspectives

Non-invasive evaluation of liver fibrosis has evolved over the last couple of decades. Currently, elastography techniques are the most widely used non-invasive methods for clinical evaluation of chronic liver disease (CLD). MR elastography (MRE) of the liver has been used in the clinical practice for nearly a decade and continues to be widely accepted for detection and staging of liver fibrosis. With MRE, one can directly visualize propagating shear waves through the liver and an inversion algorithm in the scanner automatically converts the shear wave properties into an elastogram (stiffness map) on which liver stiffness can be calculated. The commonly used MRE method, two-dimensional gradient recalled echo (2D-GRE) sequence has produced excellent results in the evaluation of liver fibrosis in CLD from various etiologies and newer clinical indications continue to emerge. Advances in MRE technique, including 3D MRE, automated liver elasticity calculation, improvements in shear wave delivery and patient experience, are promising to provide a faster and more reliable MRE of liver. Innovations, including evaluation of mechanical parameters, such as loss modulus, displacement, and volumetric strain, are promising for comprehensive evaluation of CLD as well as understanding pathophysiology, and in differentiating various etiologies of CLD. In this review, the current status of the MRE of liver in CLD are outlined and followed by a brief description of advanced techniques and innovations in MRE of liver.

Three Distinct Stroma Types in Human Pancreatic Cancer Identified by Image Analysis of Fibroblast Subpopulations and Collagen

PURPOSE

Cancer-associated fibroblasts have emerged to be highly heterogenous and can play multifaceted roles in dictating pancreatic ductal adenocarcinoma (PDAC) progression, immunosuppression, and therapeutic response, highlighting the need for a deeper understanding of stromal heterogeneity between patients and even within a single tumor. We hypothesized that image analysis of fibroblast subpopulations and collagen in PDAC tissues might guide stroma-based patient stratification to predict clinical outcomes and tumor characteristics.

EXPERIMENTAL DESIGN

A novel multiplex IHC-based image analysis system was established to digitally differentiate fibroblast subpopulations. Using whole-tissue slides from 215 treatment-naïve PDACs, we performed concurrent quantification of principal fibroblast subpopulations and collagen and defined three stroma types: collagen-rich stroma, fibroblast activation protein α (FAP)-dominant fibroblast-rich stroma, and α smooth muscle actin (ACTA2)-dominant fibroblast-rich stroma. These stroma types were assessed for the associations with cancer-specific survival by multivariable Cox regression analyses and with clinicopathologic factors, including CD8⁺ cell density.

RESULTS

FAP-dominant fibroblasts and ACTA2-dominant fibroblasts represented the principal distinct fibroblast subpopulations in tumor stroma. Stroma types were associated with patient survival, SMAD4 status, and transcriptome signatures. Compared with FAP-dominant fibroblast-rich stroma, collagen-rich stroma correlated with prolonged survival [HR, 0.57; 95% confidence interval (CI), 0.33-0.99], while ACTA2-dominant fibroblast-rich stroma exhibited poorer prognosis (HR, 1.65; 95% CI, 1.06-2.58). FAP-dominant fibroblast-rich stroma was additionally characterized by restricted CD8⁺ cell infiltrates and intense neutrophil infiltration.

CONCLUSIONS

This study identified three distinct stroma types differentially associated with survival, immunity, and molecular features, thereby underscoring the importance of stromal heterogeneity in subtyping pancreatic cancers and supporting the development of antistromal therapies.

Animal Models of Fibrosis in Nonalcoholic Steatohepatitis: Do They Reflect Human Disease?

Nonalcoholic steatohepatitis (NASH) is one of the most common chronic liver diseases in the world, yet no pharmacotherapies are available. The lack of translational animal models is a major barrier impeding elucidation of disease mechanisms and drug development. Multiple preclinical models of NASH have been proposed and can broadly be characterized as diet-induced, deficiency-induced, toxin-induced, genetically induced, or a combination of these. However, very few models develop advanced fibrosis while still reflecting human disease etiology or pathology, which is problematic since fibrosis stage is considered the best prognostic marker in patients and an important endpoint in clinical trials of NASH. While mice and rats predominate the NASH research, several other species have emerged as promising models. This review critically evaluates animal models of NASH, focusing on their ability to develop advanced fibrosis while maintaining their relevance to the human condition.

Quantification of intratumoral collagen and elastin fibers within hepatocellular carcinoma tissues finds correlations with clinico-patho-radiological features

AIM

Emerging evidence suggests a promising role for tumor stromal factors in characterizing patients with various types of malignancies, including hepatocellular carcinoma (HCC). We quantified the amount of collagen and elastin fibers in HCC samples with the aim of clarifying the clinico-patho-radiological significance of fiber deposition in HCC.

METHODS

We computed the amount of collagen and elastin fibers using digital image analysis of whole-slide images of Elastica van Gieson-stained tissues from 156 surgically resected HCCs. Furthermore, we assessed the correlations between the fiber content of HCC samples and clinical, pathological, and radiological features, including immunohistochemistry-based molecular subtypes and immunosubtypes.

RESULTS

The intratumoral area ratio of collagen in HCC tissues (median 3.4%, range 0.1-22.2%) was more than threefold that of elastin (median 0.9%, range 0.1-9.0%); there was a strong positive correlation between the amounts of collagen and elastin. Higher levels of combined collagen and elastin were significantly associated with the confluent multinodular macroscopic tumor type, the absence of a fibrous capsule, intratumoral steatosis, scirrhous tumor stroma, dense inflammatory-cell infiltrates, and the biliary/stem cell markers-positive HCC subtype. The associations of higher collagen levels with radiological findings, including heterogeneous enhancement and persistent enhancement on dynamic computed tomography, were significant. In contrast, the associations of radiological findings with elastin fibers were not significant. Intratumoral fibrous stroma in HCC comprised septum-like and perisinusoidal fibrosis; these two forms represented distinct distribution patterns of fibers and fibroblasts.

CONCLUSION

Quantitative analysis suggested that stromal fiber-rich HCCs likely represent a distinct clinico-patho-radiological entity.

Automated quantification and architectural pattern detection of hepatic fibrosis in NAFLD

Accurate detection and quantification of hepatic fibrosis remain essential for assessing the severity of non-alcoholic fatty liver disease (NAFLD) and its response to therapy in clinical practice and research studies. Our aim was to develop an integrated artificial intelligence-based automated tool to detect and quantify hepatic fibrosis and assess its architectural pattern in NAFLD liver biopsies. Digital images of the trichrome-stained slides of liver biopsies from patients with NAFLD and different severity of fibrosis were used. Two expert liver pathologists semi-quantitatively assessed the severity of fibrosis in these biopsies and using a web applet provided a total of 987 annotations of different fibrosis types for developing, training and testing supervised machine learning models to detect fibrosis. The collagen proportionate area (CPA) was measured and correlated with each of the pathologists semi-quantitative fibrosis scores. Models were created and tested to detect each of six potential fibrosis patterns. There was good to excellent correlation between CPA and the pathologist score of fibrosis stage. The coefficient of determination (R²) of automated CPA with the pathologist stages ranged from 0.60 to 0.86. There was considerable overlap in the calculated CPA across different fibrosis stages. For identification of fibrosis patterns, the models areas under the receiver operator curve were 78.6% for detection of periportal fibrosis, 83.3% for pericellular fibrosis, 86.4% for portal fibrosis and >90% for detection of normal fibrosis, bridging fibrosis, and presence of nodule/cirrhosis. In conclusion, an integrated automated tool could accurately quantify hepatic fibrosis and determine its architectural patterns in NAFLD liver biopsies.

Elastin is a key factor of tumor development in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is the most common cancer and a leading cause of death worldwide. Extracellular matrix (ECM) proteins regulate tumor growth and development in CRC. Elastin (ELN) is a component of ECM proteins involved in the tumor microenvironment. However, the role of ELN in CRC remains unclear.

METHODS

In this study, we analyzed ELN gene expression in tumors from CRC patients and adjacent non-tumor colon tissues and healthy controls from two existing microarray datasets. ELN protein was measured in human normal colon cells and colon cancer epithelial cells and tumor development was assessed in colon epithelial cells cultured in medium with or without ELN peptide on plates coated with ELN recombinant protein. Control plates were coated with PBS only.

RESULTS

We found ELN gene expression was increased in tumors from CRC patients compared to adjacent non-tumor tissues and healthy controls. ELN protein was increased in cancer cells compared to normal colon epithelial cells. Transforming growth factor beta (TGF-β) was a key cytokine to induce production of ECM proteins, but it did not induce ELN expression in colon cancer cells. Matrix metalloproteinase 9 (MMP9) gene expression was increased, but that of MMP12 (elastase) did not change between CRC patients and control. Tissue inhibitor of metalloproteinases 3 (TIMP3) gene expression was decreased in colon tissues from CRC patients compared to healthy controls. However, MMP9, MMP12 and TIMP3 proteins were increased in colon cancer cells. ELN recombinant protein increased proliferation and wound healing in colon cancer epithelial cells. This had further increased in cancer cells incubated in plates coated with recombinant ELN coated plate and in culture media containing ELN peptide. A potential mechanism was that ELN induced epithelial mesenchymal transition with increased alpha-smooth muscle actin and vimentin proteins but decreased E-cadherin protein. Tumor necrosis factor alpha (TNF) mRNA was also increased in CRC patients compared to controls. ELN recombinant protein induced further increases in TNF protein in mouse bone marrow derived macrophages after lipopolysaccharide stimulation.

CONCLUSIONS

These data suggest ELN regulates tumor development and the microenvironment in CRC.

Development of Scaffolds with Adjusted Stiffness for Mimicking Disease-Related Alterations of Liver Rigidity

Drug-induced liver toxicity is one of the most common reasons for the failure of drugs in clinical trials and frequent withdrawal from the market. Reasons for such failures include the low predictive power of in vivo studies, that is mainly caused by metabolic differences between humans and animals, and intraspecific variances. In addition to factors such as age and genetic background, changes in drug metabolism can also be caused by disease-related changes in the liver. Such metabolic changes have also been observed in clinical settings, for example, in association with a change in liver stiffness, a major characteristic of an altered fibrotic liver. For mimicking these changes in an in vitro model, this study aimed to develop scaffolds that represent the rigidity of healthy and fibrotic liver tissue. We observed that liver cells plated on scaffolds representing the stiffness of healthy livers showed a higher metabolic activity compared to cells plated on stiffer scaffolds. Additionally, we detected a positive effect of a scaffold pre-coated with fetal calf serum (FCS)-containing media. This pre-incubation resulted in increased cell adherence during cell seeding onto the scaffolds. In summary, we developed a scaffold-based 3D model that mimics liver stiffness-dependent changes in drug metabolism that may more easily predict drug interaction in diseased livers.

Corrected integrated density: a novel method for liver elastic fibers quantification in chronic hepatitis C

Background

Elastic fibers deposition is triggered during liver fibrosis and is related to worse clinical prognosis in chronic hepatitis C patients. This study aimed to verify if a new method for elastic fiber quantification can be used to discriminate between different degrees of fibrosis in liver biopsies of patients with hepatitis C.

Methods

Individuals presenting with different degrees of fibrosis in liver biopsy were included. Slides of liver samples were stained with orcein with and without prior oxidation. Morphometric analysis was proceeded, and quantification accomplished by corrected integrated density.

Results

Twenty-seven patients, mean age 52 years-old, 59% women, were included. Elastic fibers density was higher in advanced fibrosis patients and there was a positive correlation with Metavir score (Spearman r = 0.609, p < 0.001), as well as with the noninvasive scores Fib-4 (Pearson r = 0.46, p = 0.029) and APRI (r = 0.52, p = 0.01).

Conclusion

Morphometric analysis by corrected integrated density demonstrates that elastic fibers abundance is higher in advanced stage of fibrosis in patients with hepatitis C.

Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders

Histological analysis of hepatic tissue specimens is essential for evaluating the pathology of several liver disorders such as chronic liver diseases, hepatocellular carcinomas, liver steatosis, and infectious liver diseases. Manual examination of histological slides on the microscope is a classically used method to study these disorders. However, it is considered time-consuming, limited, and associated with intra- and inter-observer variability. Emerging technologies such as whole slide imaging (WSI), also termed virtual microscopy, have increasingly been used to improve the assessment of histological features with applications in both clinical and research laboratories. WSI enables the acquisition of the tissue morphology/pathology from glass slides and translates it into a digital form comparable to a conventional microscope, but with several advantages such as easy image accessibility and storage, portability, sharing, annotation, qualitative and quantitative image analysis, and use for educational purposes. WSI-generated images simultaneously provide high resolution and a wide field of observation that can cover the entire section, extending any single field of view. In this review, we summarize current knowledge on the application of WSI to histopathological analyses of liver disorders as well as to understand liver biology. We address how WSI may improve the assessment and quantification of multiple histological parameters in the liver, and help diagnose several hepatic conditions with important clinical implications. The WSI technical limitations are also discussed.

Precision pathology analysis of the development and progression of hepatocellular carcinoma: Implication for precision diagnosis of hepatocellular carcinoma

Outcomes for patients with hepatocellular carcinoma (HCC) remain poor because the condition is often unresponsive to the available treatments. Consequently, the early and precise diagnosis of HCC is crucial to achieve improvements in prognosis. For patients with chronic liver disease, the assessment of liver fibrosis is also important to ascertain both the staging of fibrosis and the risk of HCC occurrence. Early HCC was first described in 1991 in Japan and was defined internationally in 2009. As the concept of early HCC spread, the multistage hepatocarcinogenesis process became accepted. Consequently, improvements in imaging technology made the early diagnosis of HCC possible. At present, the most appropriate therapeutic strategy for HCC is determined using an integrated staging system that assesses the tumor burden, the degree of liver dysfunction and the patient performance status; however, pathological and molecular features are not taken into account. The recent introduction of several new therapeutic agents will change the treatment strategy for HCC. Against this background, HCC subclassification based on tumor cellular and microenvironmental characteristics will become increasingly important. In this review, we give an overview of how pathological analysis contributes to understanding the development and progression of HCC and establishing a precision diagnosis of HCC.

Transient elastography: should XL probe be used in all overweight patients?

Background: Obesity is one of the main factors of transient elastography (TE) failure, considering body mass index (BMI) ≥28 kg/m2 as a limiting factor. The XL probe was designed to overcome this limitation. Aim: To compare the feasibility of the M and XL probes in patients with BMI ≥ 28 kg/m2, to evaluate differences in mean values of controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) between the two probes and find predictive factors of TE failure. Material and methods: Prospective study, including all patients with BMI ≥ 28 kg/m2 consecutively admitted for TE. Results: Included 161 patients. Measurements with M probe were reliable in 69.6% of the patients, with 68.2% of valid measurements in obese population and 58.9% in patients with skin-capsule distance (SCD) >25 mm. In 40 patients (81.6%) with an invalid M probe measurement, a reliable result was obtained with XL probe. We found that SCD >25 mm was the only predictor of M probe failure (OR: 4.9, CI: 1.64-14.63, p = .004). In those patients in which TE was possible with both probes (n = 112), mean CAP was 304 ± 49 dB/m2 with M probe and 301 ± 50 dB/m2 with XL probe (p = .59). Regarding liver stiffness, a mean value of 7.58 ± 3.47 kpas was obtained with the M probe and 6.21 ± 3.44 kpas with the XL probe (p < .001). Conclusion: There is a reliable applicability of the M probe in a high number (68.2%) of patients with a BMI ≥30 kg/m2. A SCD >25 mm was the only predictive factor of M probe failure. Mean values of LSM with XL probe were lower than those obtained with M probe.

Dynamics of elastin in liver fibrosis: Accumulates late during progression and degrades slowly in regression

Elastin is an amorphous protein highly resistant to elastase degradation and is believed to be the most stable component among the extracellular matrix (ECM) members. Thus the excessive deposition of elastin in advanced liver fibrosis may contribute to the declining reversibility of the disease. Our previous study has found that elastin crosslinking inhibition can effectively arrest liver fibrosis progression. To further understand the roles of elastin involved in liver fibrosis, we systematically investigated the expression, accumulation, and degradation based on dynamic and bidirectional CCl₄ -induced liver fibrosis mouse models and visualized the ultrastructure of elastin globules in cultured LX-2 cells. We found that the expression pattern of tropoelastin (soluble elastin) and collagen I was not completely comparable at both the transcriptional and posttranscriptional levels during liver fibrosis progression and regression. Elastin mainly accumulated onto the internodular fibrous septa and enlarged portal areas and intertwined with collagen I at the late stage of liver fibrosis. Three-dimensional analysis of elastin and collagen I by confocal immunofluorescence coupled with biochemical analyses revealed that with respect to collagen, elastin deposition was characterized by late aggregation in progression and slow turnover in regression. In addition, we visualized the dynamic ultrastructure of ECM fibers during liver fibrogenesis and fibrolysis and the ultrastructure of elastin globules self-aggregated by tropoelastin crosslinking. Our current study established new general hallmarks of elastin levels and forms in progressive and regressive liver fibrosis and provided a foundation for further experimental investigation of the growing role of elastin in liver fibrosis regression.

Histological and biochemical changes induced by gibberellic acid in the livers of pregnant albino rats and their offspring: ameliorative effect of Nigella sativa

Gibberellic acid (GA3), a plant growth regulator, is widely used in agriculture in many countries to accelerate the growth of fruits and vegetables. We designed histological, immunohistochemical, and biochemical studies to evaluate the deleterious effects of GA3 on the livers of adult pregnant rats and their offspring and to assess the possible ameliorative effect of Nigella sativa Linn. (NsL.oil) against these effects. Twenty-four pregnant albino rats were utilized, randomly divided into four groups: The first group was used as a negative control group, while the second group (positive control group) was provided NsL.oil at a dose of 100 mg/kg of bodyweight. Animals in the third group (GA3 group) were provided 200 ppm of GA3 dissolved in distilled water from the 7th day of pregnancy until 1 day after delivery. Animals in the last group (GA3 + NsL.oil group) were provided GA3 and NsL-oil at the same doses as mentioned above. One day after delivery, each group of lactating mothers and their pups were sacrificed. Liver specimens were subjected to histopathological, immunohistochemical, and biochemical examinations. The livers of rats from the GA3 group showed various degenerative changes, being predominant in the livers of the mothers compared with the offspring. The pathological changes in the livers of the offspring suggested transplacental passage of GA3. The results reveal that GA3 ingestion induced a significant increase in alanine aminotransferase (ALT) and aspartate transaminase (AST) activities in the serum of both groups of mothers and their pups, with a significant increment in lipid peroxidation as evidenced by enhanced malondialdehyde (MDA) levels with significant decrements in superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) enzymatic activities in comparison with control groups in the liver of mothers and their offspring. Histopathological examination showed hydropic degeneration and inflammatory cellular infiltration. Additionally, there was fibrosis around the portal area. Moreover, immunolocalization revealed downregulation of the expression of the antiapoptotic marker Bcl-2 in hepatocytes and upregulation of the expression of the apoptotic marker Bax in the treated group. Concomitant use of NsL.oil along with GA3 exerted a considerable reversing effect on histopathological and biochemical changes in the livers of mother groups and their pups. The results of the present study highlight the consequences of exposure to GA3 during pregnancy on hepatic tissue in both mothers and their offspring. Furthermore, the study suggests use of NsL.oil as a potential protective strategy against GA3-induced liver toxicity.

Collagen proportionate area is an independent predictor of long-term outcome in patients with non-alcoholic fatty liver disease

BACKGROUND

Collagen proportionate area (CPA) measurement is a technique that quantifies fibrous tissue in liver biopsies by measuring the amount of collagen deposition as a proportion of the total biopsy area. CPA predicts clinical outcomes in patients with HCV and can sub-classify cirrhosis.

AIM

To test the ability of CPA to quantify fibrosis and predict clinical outcomes in patients with NAFLD.

METHODS

We assessed consecutive patients with biopsy-proven NAFLD from three European centres. Clinical and laboratory data were collected at baseline and at the time of the last clinical follow-up or death. CPA was performed at two different objective magnifications, whole biopsy macro and ×4 objective magnification, named standard (SM) and high (HM) magnification respectively. The correlation between CPA and liver stiffness was assessed in a sub-group of patients.

RESULTS

Of 437 patients, 32 (7.3%) decompensated and/or died from liver-related causes during a median follow-up of 103 months. CPA correlated with liver stiffness and liver fibrosis stage across the whole spectrum of fibrosis. HM CPA was significantly higher than SM CPA in stages F0-F3 but similar in cirrhosis, reflecting a higher ability to capture pericellular/perisinusoidal fibrosis at early stages. Age at baseline (HR: 1.04, 95% CI: 1.01-1.08), HM CPA (HR: 1.04 per 1% increase, 95% CI: 1.01-1.08) and presence of advanced fibrosis (HR: 15.4, 95% CI: 5.02-47.84) were independent predictors of liver-related clinical outcomes at standard and competing risk multivariate Cox-regression analysis.

CONCLUSIONS

CPA accurately measures fibrosis and is an independent predictor of clinical outcomes in NAFLD; hence it merits further evaluation as a surrogate endpoint in clinical trials.

Predictive Values of Serum Uric Acid and Alanine-aminotransferase for Fatty Liver Index in Montenegrin Population

Background

Alanine-aminotransferase (ALT) and uric acid cut-off levels used in non-alcoholic fatty liver disease (NAFLD) diagnosis are advised to be lowered. Due to contradictory results on the utility of both these biomarkers for NAFLD screening, we aimed to determine their cut-off levels that can be applied to Montenegrin population with the fatty liver disease.

Methods

A total of 771 volunteers were enrolled. A fatty liver index (FLI) score ≥60 was used as proxy of NAFLD. The receiver operating characteristic curve analysis with the area under the curve (AUC) was used to determine the cut-off values of ALT and uric acid associated with FLI ≥60.

Results

ALT was independent predictor of FLI in both men and women, whereas serum uric acid was its independent predictor only in women. Lower cut-off levels of ALT are associated with the increased prevalence of NAFLD [i.e., ALT was 19 IU/L (AUC=0.746, sensitivity 63%, specificity 72%, P<0.001) in women and 22 IU/L (AUC=0.804, sensitivity 61%, specificity 95%, P<0.001) in men]. The cut-off value for uric acid was 274 μmol/L (AUC=0.821, sensitivity 68%, specificity 82%, P<0.001) in women.

Conclusions

Lower cut-off levels of ALT in both genders, and serum uric acid in females, can be reliable predictors of the FLI.

The Forkhead box F1 transcription factor inhibits collagen deposition and accumulation of myofibroblasts during liver fibrosis

Hepatic fibrosis is the common end stage to a variety of chronic liver injuries and is characterized by an excessive deposition of extracellular matrix (ECM), which disrupts the liver architecture and impairs liver function. The fibrous lesions are produced by myofibroblasts, which differentiate from hepatic stellate cells (HSC). The myofibroblast's transcriptional networks remain poorly characterized. Previous studies have shown that the Forkhead box F1 (FOXF1) transcription factor is expressed in HSCs and stimulates their activation during acute liver injury; however, the role of FOXF1 in the progression of hepatic fibrosis is unknown. In the present study, we generated αSMACreER;Foxf1fl/fl mice to conditionally inactivate Foxf1 in myofibroblasts during carbon tetrachloride-mediated liver fibrosis. Foxf1 deletion increased collagen depositions and disrupted liver architecture. Timp2 expression was significantly increased in Foxf1-deficient mice while MMP9 activity was reduced. RNA sequencing of purified liver myofibroblasts demonstrated that FOXF1 inhibits expression of pro-fibrotic genes, Col1α2, Col5α2, and Mmp2 in fibrotic livers and binds to active repressors located in promotors and introns of these genes. Overexpression of FOXF1 inhibits Col1a2, Col5a2, and MMP2 in primary murine HSCs in vitro Altogether, FOXF1 prevents aberrant ECM depositions during hepatic fibrosis by repressing pro-fibrotic gene transcription in myofibroblasts and HSCs.

Non-invasive liver fibrosis assessment correlates with collagen and elastic fiber quantity in patients with hepatitis C virus infection

AIM

Elastic fiber deposition is a cause of irreversibility of liver fibrosis. However, to date, its relevance to clinical features has not yet been clarified. This study aimed to clarify the correlation between non-invasive markers of fibrosis and fiber quantity, including elastic fiber, obtained from computational analysis.

METHODS

This retrospective study included 270 patients evaluated by non-invasive liver fibrosis assessment prior to liver biopsy. Of these patients, 95 underwent magnetic resonance elastography (MRE) and 244 were assessed with Wisteria floribunda agglutinin-positive Mac-2 binding protein (WFA⁺ -M2BP). Using whole-slide imaging of Elastica van Gieson-stained liver biopsy sections, the quantity of collagen, elastin, and total fiber (elastin + collagen) was determined.

RESULTS

The total fiber quantity showed significant linear correlation with fibrosis stage F0-F4. Collagen fiber quantity increased from stage F0 to F4, whereas elastic fiber quantity increased significantly only from stage F2 to F3. Spearman's rank correlation test revealed that non-invasive liver fibrosis assessment significantly correlates with each fiber quantity, including correlation between total fiber quantity and the Fibrosis-4 (FIB-4) index (r = 0.361, P < 0.001), WFA⁺ -M2BP values (r = 0.404, P < 0.001), and liver stiffness value by MRE (r = 0.615, P < 0.001). Receiver operating characteristic (ROC) curve analyses revealed that the area under ROC for predicting higher elastic fiber (>3.6%) is 0.731 by FIB-4 index, 0.716 by WFA⁺ -M2BP, and 0.822 by liver stiffness by MRE.

CONCLUSION

Liver fibrosis correlates with fiber quantity through non-invasive assessment regardless of fiber type, including elastic fiber. Moreover, MRE is useful for predicting high amounts of elastic fiber.