Image analysis of liver biopsy samples measures fibrosis and predicts clinical outcome

Integrating Molecular Testing With Clinical Criteria and Histopathology Improves Diagnostic Precision in Immune-Mediated Liver Diseases

Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are immune-mediated liver diseases (IMLDs) that are diagnosed by a combination of clinical, serologic, and histologic features. Diagnosis may be challenging, particularly when patients have mixed features of both AIH and PBC, a disease often called overlap syndrome (OS). In addition, many patients have refractory disease. We hypothesized that adding molecular testing to the current diagnostic criteria would provide an additional tool that could assist in correctly classifying patients. RNA was isolated from liver biopsies from patients with AIH (n = 16), PBC (n = 13), OS (n = 8), drug-induced/serology-negative AIH (AIH DI/Ser-neg, n = 6), or controls (n = 10). Gene expression was determined using an nCounter Sprint Profiler, and principal component analysis delineated distinct clusters for patients with an inflammatory profile due to AIH, PBC, and AIH DI/Ser-neg. Two patients with minimal histologic features of PBC clustered with the control group, and 2 patients with predominantly AIH and minimal PBC features clustered with the PBC group. A patient with OS who received treatment for both conditions showed no disease progression, whereas a patient with OS treated solely for AIH failed to respond. Conversely, one of the gene signatures from a patient diagnosed with PBC fell within the AIH group. This patient did not respond to treatment with ursodiol and ultimately required liver replacement. These findings suggest that the IMLD initially diagnosed in these patients may have been incorrectly classified. As expected, molecular analysis could not identify a distinct cluster for patients diagnosed with OS, and these had variable gene signatures that fell throughout the identified AIH or PBC groups. Cluster analysis was also able to distinguish patients with disease progression from non-progressors with mild disease who responded to treatment. In summary, gene expression analysis may assist in confirming the type of IMLD, especially when the diagnosis is unclear. Combining molecular testing with existing criteria could provide an additional diagnostic tool, improving patient care and response to treatment.

Integrative proteo-transcriptomic characterization of advanced fibrosis in chronic liver disease across etiologies

Chronic hepatic injury and inflammation from various causes can lead to fibrosis and cirrhosis, potentially predisposing to hepatocellular carcinoma. The molecular mechanisms underlying fibrosis and its progression remain incompletely understood. Using a proteo-transcriptomics approach, we analyze liver and plasma samples from 330 individuals, including 40 healthy individuals and 290 patients with histologically characterized fibrosis due to chronic viral infection, alcohol consumption, or metabolic dysfunction-associated steatotic liver disease. Our findings reveal dysregulated pathways related to extracellular matrix, immune response, inflammation, and metabolism in advanced fibrosis. We also identify 132 circulating proteins associated with advanced fibrosis, with neurofascin and growth differentiation factor 15 demonstrating superior predictive performance for advanced fibrosis(area under the receiver operating characteristic curve [AUROC] 0.89 [95% confidence interval (CI) 0.81-0.97]) compared to the fibrosis-4 model (AUROC 0.85 [95% CI 0.78-0.93]). These findings provide insights into fibrosis pathogenesis and highlight the potential for more accurate non-invasive diagnosis.

Evaluation of Aortic Hemodynamics Using Four-Dimensional Flow of Magnetic Resonance Imaging in Rabbits with Liver Fibrosis

BACKGROUND

Liver fibrosis (LF) precipitates systemic hemodynamic alterations, however, its impact on the aorta remaining undefined.

PURPOSE

To assess aorta hemodynamics changes during LF development in a rabbit model.

STUDY TYPE

Prospective, experimental.

ANIMAL MODEL

Thirty 7-month-old male rabbits underwent bile duct ligation (BDL) to induce LF.

FIELD STRENGTH/SEQUENCE

Biweekly four-dimensional (4D) flow imaging incorporating a 3D gradient-echo at 3.0 T scanner for 14 weeks post-BDL.

ASSESSMENT

Histopathological exams for 2-5 rabbits were performed at each time point, following each MRI scan. LF was graded using the Metavir scale by a pathologist. 4D flow was analyzed by two radiologists using dedicated postprocessing software. They recorded 4D flow parameters at four aorta sections (aortic sinus, before and after bifurcation of aortic arch, and descending aorta).

STATISTICAL TESTS

The linear mixed model; Bonferroni correction; Pearson correlation coefficient (r); receiver operating characteristic (ROC) curve; Delong test. The level of significance was set at P < 0.05.

RESULTS

Following BDL, the wall shear stress (WSS) (0.23-0.32 Pa), energy loss (EL) (0.27-1.55 mW) of aorta significantly increased at the second week for each plane, peaking at the sixth week (WSS: 0.35-0.49 Pa, EL: 0.57-2.0 mW). So did the relative pressure difference (RPD) (second week: 1.67 ± 1.63 mmHg, sixth week: 2.43 ± 0.63 mmHg) in plane 2. Notably, the RPD in plane 2 at the second week displayed the highest area under ROC curve of 0.998 (specificity: 1, sensitivity: 0.967). LF were found at the second, fourth, and sixth week after BDL, with grade F2, F3, and F4, respectively. The RPD in plane 2 was most strongly correlated with the severity of LF (r = 0.86).

DATA CONCLUSIONS

The occurrence of LF could increase WSS, EL, and RPD of aorta as early as the second week following BDL.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 2.

Assessment of the Fibrosis Score and the Child-Turcotte-Pugh (CTP) Score in Patients With Chronic Liver Disease in India

OBJECTIVE

 This study aimed to evaluate the severity of liver fibrosis in chronic liver disease patients using aspartate aminotransferase-to-platelet ratio index (APRI), fibrosis-4 (FIB-4), FibroScan, and the Child-Turcotte-Pugh (CTP) score. It emphasized assessing fibrosis progression toward cirrhosis (F4 stage) and exploring the correlation between non-invasive markers and the CTP score for liver function and prognosis.

METHODOLOGY

This observational cross-sectional study was conducted over one calendar year in the Department of Medicine at Baba Raghav Das (BRD) Medical College, Gorakhpur, India. A total of 200 patients with chronic liver disease were selected. Fibrosis scores were calculated using FibroScan, APRI, and FIB-4, while the modified CTP score was determined for each participant. Pearson's correlation was used to assess relationships between variables, while logistic regression evaluated the association of non-invasive methods (APRI, FIB-4, FibroScan) with severe fibrosis (F4). Odds ratios (ORs), sensitivity, specificity, and AUC were calculated, and ROC curves visualized their discriminative ability. Statistical significance was defined as p < 0.05.

RESULTS

 The study revealed a predominance of advanced fibrosis (F4) in males (82.5%) and patients with ethanol-induced liver disease (84.6%). FIB-4 had the strongest predictive value for advanced fibrosis with an OR of 3.8 (95% CI: 3.0-4.5) and AUC of 0.743, followed by APRI with an OR of 2.5 (95% CI: 1.9-3.1) and AUC of 0.757. CTP showed the highest sensitivity (95.45%) but a lower AUC (0.697), indicating its clinical value in correlating fibrosis severity with liver dysfunction. Hemoglobin, platelets, and INR showed no significant correlation with fibrosis, while total bilirubin was elevated in advanced CTP classes. A moderate positive correlation (r = 0.481, p < 0.001) was observed between fibrosis scores and CTP, linking fibrosis severity with liver dysfunction. These findings emphasize FIB-4's superior predictive accuracy, while APRI and CTP remain valuable complementary tools for liver disease prognosis.

CONCLUSION

 In conclusion, FIB-4 is the most accurate for staging advanced fibrosis, while APRI excels in initial screening due to its higher sensitivity. FibroScan effectively assesses direct fibrosis, and the CTP score adds prognostic value, making these methods complementary for managing chronic liver diseases.

Collagen in hepatocellular carcinoma: A novel biomarker and therapeutic target

HCC is globally recognized as a major health threat. Despite significant progress in the development of treatment strategies for liver cancer, recurrence, metastasis, and drug resistance remain key factors leading to a poor prognosis for the majority of liver cancer patients. Thus, there is an urgent need to develop effective biomarkers and therapeutic targets for HCC. Collagen, the most abundant and diverse protein in the tumor microenvironment, is highly expressed in various solid tumors and plays a crucial role in the initiation and progression of tumors. Recent studies have shown that abnormal expression of collagen in the tumor microenvironment is closely related to the occurrence, development, invasion, metastasis, drug resistance, and treatment of liver cancer, making it a potential therapeutic target and a possible diagnostic and prognostic biomarker for HCC. This article provides a comprehensive review of the structure, classification, and origin of collagen, as well as its role in the progression and treatment of HCC and its potential clinical value, offering new insights into the diagnosis, treatment, and prognosis assessment of liver cancer.

The prediction of liver decompensation using hepatic collagen deposition assessed by computer-assisted image analysis with Masson's trichrome stain

BACKGROUND & AIM

The current pathologic system classifies structural deformation caused by hepatic fibrosis semi-quantitatively, which may lead to a disagreement among pathologists. We measured hepatic fibrosis quantitatively using collagen proportionate area (CPA) in compensated cirrhotic patients and assessed its impact on predicting the development of liver decompensation.

METHOD

From January 2010 to June 2018, we assessed 101 patients who went through liver biopsy and received diagnosis as compensated cirrhosis with digital image analysis of CPA. Clinical and laboratory data were collected at the baseline and at the time of the last follow-up or progression to liver decompensation (LD).

RESULT

The mean age was 50.8 ± 10.5 years, and the most common etiology of liver disease was chronic hepatitis B (48.5%), followed by alcoholic hepatitis (18.8%). The mean CPA was 16.91 ± 9.60%. The mean CPA values were different in patients with and without LD development (21.8 ± 11.1 vs. 15.2 ± 8.5). During the median follow-up of 60.0 months, 26 out of 101 patients experienced LD. Older age (hazard ratio [HR],1.069; p = 0.015), prolonged international normalized ratio (HR, 6.449; p = 0.019) and higher CPA (HR, 1.049; p = 0.040) were independent predictors of liver decompensation on multivariate cox-regression analysis. When patients were divided according to the optimal CPA threshold (26.8%), higher CPA predicted LD better than lower CPA. (Log-rank test: p < 0.001).

CONCLUSION

CPA could be a useful quantitative prognostic value for patients with compensated cirrhosis.

Liver fibrosis quantified by image morphometry predicts clinical outcomes in patients with non-alcoholic fatty liver disease

BACKGROUND AND AIMS

Liver fibrosis predicts adverse clinical outcomes, such as liver-related death (LRD) and hepatocellular carcinoma (HCC) in patients with non-alcoholic fatty liver disease (NAFLD). We aimed to investigate the accuracy of semi-automated quantification of collagen proportionate area (CPA) as an objective new method for predicting clinical outcomes.

METHOD

Liver biopsies from patients with NAFLD underwent computerized image morphometry of Sirius Red staining with CPA quantification performed by ImageScope. Clinical outcomes, including total mortality, LRD, and combined liver outcomes (liver decompensation, HCC, or LRD), were determined by medical records and population-based data-linkage. The accuracy of CPA for predicting outcomes was compared with non-invasive fibrosis tests (Hepascore, FIB-4, APRI).

RESULTS

A total of 295 patients (mean age 50 years) were followed for a median (range) of 9 (0.2-25) years totalling 3253 person-years. Patients with CPA ≥ 10% had significantly higher risks for total death [hazard ratio (HR): 5.0 (1.9-13.2)], LRD [19.0 (2.0-182.0)], and combined liver outcomes [15.6 (3.1-78.6)]. CPA and pathologist fibrosis staging (FS) showed similar accuracy (AUROC) for the prediction of total death (0.68 vs. 0.70), LRD (0.72 vs. 0.77) and combined liver outcomes (0.75 vs. 0.78). Non-invasive serum markers Hepascore, APRI, and FIB-4 reached higher AUROC; however, they were not statistically significant compared to that of CPA except for Hepascore in predicting total mortality (0.86 vs. 0.68, p = 0.009).

CONCLUSION

Liver fibrosis quantified by CPA analysis was significantly associated with clinical outcomes including total mortality, LRD, and HCC. CPA achieved similar accuracy in predicting outcomes compared to pathologist fibrosis staging and non-invasive serum markers.

Practical diagnosis of cirrhosis in non-alcoholic fatty liver disease using currently available non-invasive fibrosis tests

Unlike for advanced liver fibrosis, the practical rules for the early non-invasive diagnosis of cirrhosis in NAFLD remain not well defined. Here, we report the derivation and validation of a stepwise diagnostic algorithm in 1568 patients with NAFLD and liver biopsy coming from four independent cohorts. The study algorithm, using first the elastography-based tests Agile3+ and Agile4 and then the specialized blood tests FibroMeterV3G and CirrhoMeterV3G, provides stratification in four groups, the last of which is enriched in cirrhosis (71% prevalence in the validation set). A risk prediction chart is also derived to allow estimation of the individual probability of cirrhosis. The predicted risk shows excellent calibration in the validation set, and mean difference with perfect prediction is only -2.9%. These tools improve the personalized non-invasive diagnosis of cirrhosis in NAFLD.

Assessment of compensated advanced chronic liver disease based on serum bile acids in chronic hepatitis B patients

Patients with chronic liver disease progressed to compensated advanced chronic liver disease (cACLD), the risk of liver-related decompensation increased significantly. This study aimed to develop prediction model based on individual bile acid (BA) profiles to identify cACLD. This study prospectively recruited 159 patients with hepatitis B virus (HBV) infection and 60 healthy volunteers undergoing liver stiffness measurement (LSM). With the value of LSM, patients were categorized as three groups: F1 [LSM ≤ 7.0 kilopascals (kPa)], F2 (7.1 < LSM ≤ 8.0 kPa), and cACLD group (LSM ≥ 8.1 kPa). Random forest (RF) and support vector machine (SVM) were applied to develop two classification models to distinguish patients with different degrees of fibrosis. The content of individual BA in the serum increased significantly with the degree of fibrosis, especially glycine-conjugated BA and taurine-conjugated BA. The Marco-Precise, Marco-Recall, and Marco-F1 score of the optimized RF model were all 0.82. For the optimized SVM model, corresponding score were 0.86, 0.84, and 0.85, respectively. RF and SVM models were applied to identify individual BA features that successfully distinguish patients with cACLD caused by HBV. This study provides a new tool for identifying cACLD that can enable clinicians to better manage patients with chronic liver disease.

Risk stratification and early detection biomarkers for precision HCC screening

Hepatocellular carcinoma (HCC) mortality remains high primarily due to late diagnosis as a consequence of failed early detection. Professional societies recommend semi-annual HCC screening in at-risk patients with chronic liver disease to increase the likelihood of curative treatment receipt and improve survival. However, recent dynamic shift of HCC etiologies from viral to metabolic liver diseases has significantly increased the potential target population for the screening, whereas annual incidence rate has become substantially lower. Thus, with the contemporary HCC etiologies, the traditional screening approach might not be practical and cost-effective. HCC screening consists of (i) definition of rational at-risk population, and subsequent (ii) repeated application of early detection tests to the population at regular intervals. The suboptimal performance of the currently available HCC screening tests highlights an urgent need for new modalities and strategies to improve early HCC detection. In this review, we overview recent developments of clinical, molecular, and imaging-based tools to address the current challenge, and discuss conceptual framework and approaches of their clinical translation and implementation. These encouraging progresses are expected to transform the current "one-size-fits-all" HCC screening into individualized precision approaches to early HCC detection and ultimately improve the poor HCC prognosis in the foreseeable future.

Unpaired virtual histological staining using prior-guided generative adversarial networks

Fibrosis is an inevitable stage in the development of chronic liver disease and has an irreplaceable role in characterizing the degree of progression of chronic liver disease. Histopathological diagnosis is the gold standard for the interpretation of fibrosis parameters. Conventional hematoxylin-eosin (H&E) staining can only reflect the gross structure of the tissue and the distribution of hepatocytes, while Masson trichrome can highlight specific types of collagen fiber structure, thus providing the necessary structural information for fibrosis scoring. However, the expensive costs of time, economy, and patient specimens as well as the non-uniform preparation and staining process make the conversion of existing H&E staining into virtual Masson trichrome staining a solution for fibrosis evaluation. Existing translation approaches fail to extract fiber features accurately enough, and the decoder of staining is unable to converge due to the inconsistent color of physical staining. In this work, we propose a prior-guided generative adversarial network, based on unpaired data for effective Masson trichrome stained image generation from the corresponding H&E stained image. Conducted on a small training set, our method takes full advantage of prior knowledge to set up better constraints on both the encoder and the decoder. Experiments indicate the superior performance of our method that surpasses the previous approaches. For various liver diseases, our results demonstrate a high correlation between the staging of real and virtual stains (ρ=0.82; 95% CI: 0.73-0.89). In addition, our finetuning strategy is able to standardize the staining color and release the memory and computational burden, which can be employed in clinical assessment.

Patients with fibrosis from non-alcoholic steatohepatitis have heterogeneous intrahepatic macrophages and therapeutic targets

Background and Aims

In clinical trials for reducing fibrosis in NASH patients, therapeutics that target macrophages have had variable results. We evaluated intrahepatic macrophages in patients with non-alcoholic steatohepatitis to determine if fibrosis influenced phenotypes and expression of CCR2 and Galectin-3.

Approach & Results

We used nCounter to analyze liver biopsies from well-matched patients with minimal (n=12) or advanced (n=12) fibrosis to determine which macrophage-related genes would be significantly different. Known therapy targets (e.g., CCR2 and Galectin-3) were significantly increased in patients with cirrhosis.However, several genes (e.g., CD68, CD16, and CD14) did not show significant differences, and CD163, a marker of pro-fibrotic macrophages was significantly decreased with cirrhosis. Next, we analyzed patients with minimal (n=6) or advanced fibrosis (n=5) using approaches that preserved hepatic architecture by multiplex-staining with anti-CD68, Mac387, CD163, CD14, and CD16. Spectral data were analyzed using deep learning/artificial intelligence to determine percentages and spatial relationships. This approach showed patients with advanced fibrosis had increased CD68+, CD16+, Mac387+, CD163+, and CD16+CD163+ populations. Interaction of CD68+ and Mac387+ populations was significantly increased in patients with cirrhosis and enrichment of these same phenotypes in individuals with minimal fibrosis correlated with poor outcomes. Evaluation of a final set of patients (n=4) also showed heterogenous expression of CD163, CCR2, Galectin-3, and Mac387, and significant differences were not dependent on fibrosis stage or NAFLD activity.

Conclusions

Approaches that leave hepatic architecture intact, like multispectral imaging, may be paramount to developing effective treatments for NASH. In addition, understanding individual differences in patients may be required for optimal responses to macrophage-targeting therapies.

Significance of interstitial fibrosis and p16 in papillary thyroid carcinoma

We enrolled 264 patients with papillary thyroid carcinoma (PTC). We performed immunohistochemical detection of p16 and determined the degree of interstitial fibrosis (IF). The expression of p16 was associated with pathological tumor-node-metastasis (pTNM) stage and age (p < 0.05). The cancer-specific survival (CSS) was longer in p16-negative patients (195.73 vs. 181.78 months, p = 0.007). p16 was significantly related to the degree of IF (r = 0.130, p = 0.035). PTC patients with no or mild fibrosis tended to have a larger tumor (p = 0.045). The degree of fibrosis was related to the proportion of papillary structure components (p = 0.025). Univariate and multivariate survival analyses showed that relapse-free survival (RFS) was longer in patients with moderate/severe IF (p < 0.05). In summary, p16 was correlated with prognosis and IF of PTC. Patients with moderate/severe IF tend to have better prognosis in RFS.

Serum non-coding RNAs for diagnosis and stage of liver fibrosis

Background

All chronic liver diseases could lead to liver fibrosis. Accurate diagnosis and stage of fibrosis were important for the medical determination, management, and therapy. Liver biopsy was considered to be the gold criteria of fibrosis diagnosis. However, liver biopsy was an invasive method with some drawbacks. Non‐invasive tests for liver fibrosis included radiologic method and serum‐based test. Radiologic examination was influenced by obesity, cost, and availability. Serum‐based test was widely used in the screening and diagnostic of liver fibrosis. However, the accuracy was still needed to be improved.

Methods

Recent studies showed serum non‐coding RNAs: microRNA, long non‐coding RNA(lncRNA), and circular RNA(circRNA), which have the potentiality to be non‐invasive markers for liver fibrosis. The recent progress was summarized in this review.

Results

These studies showed serum non‐coding RNAs exerted a good diagnostic performance for liver fibrosis. A panel that included several non‐coding RNAs could increase the accuracy of single marker.

Conclusions

Serum microRNAs, lncRNAs, and circRNAs could be potential non‐invasive markers for diagnosis and stage of liver fibrosis. More high‐quality clinical study is needed for further research.

Recent Advancements in Antifibrotic Therapies for Regression of Liver Fibrosis

Cirrhosis is a severe form of liver fibrosis that results in the irreversible replacement of liver tissue with scar tissue in the liver. Environmental toxicity, infections, metabolic causes, or other genetic factors including autoimmune hepatitis can lead to chronic liver injury and can result in inflammation and fibrosis. This activates myofibroblasts to secrete ECM proteins, resulting in the formation of fibrous scars on the liver. Fibrosis regression is possible through the removal of pathophysiological causes as well as the elimination of activated myofibroblasts, resulting in the reabsorption of the scar tissue. To date, a wide range of antifibrotic therapies has been tried and tested, with varying degrees of success. These therapies include the use of growth factors, cytokines, miRNAs, monoclonal antibodies, stem-cell-based approaches, and other approaches that target the ECM. The positive results of preclinical and clinical studies raise the prospect of a viable alternative to liver transplantation in the near future. The present review provides a synopsis of recent antifibrotic treatment modalities for the treatment of liver cirrhosis, as well as a brief summary of clinical trials that have been conducted to date.

Two-dimensional shear wave elastography predicts survival in advanced chronic liver disease

OBJECTIVE

Liver stiffness measurement (LSM) is a tool used to screen for significant fibrosis and portal hypertension. The aim of this retrospective multicentre study was to develop an easy tool using LSM for clinical outcomes in advanced chronic liver disease (ACLD) patients.

DESIGN

This international multicentre cohort study included a derivation ACLD patient cohort with valid two-dimensional shear wave elastography (2D-SWE) results. Clinical and laboratory parameters at baseline and during follow-up were recorded. LSM by transient elastography (TE) was also recorded if available. The primary outcome was overall mortality. The secondary outcome was the development of first/further decompensation.

RESULTS

After screening 2148 patients (16 centres), 1827 patients (55 years, 62.4% men) were included in the 2D-SWE cohort, with median liver SWE (L-SWE) 11.8 kPa and a model for end stage liver disease (MELD) score of 8. Combination of MELD score and L-SWE predict independently of mortality (AUC 0.8). L-SWE cut-off at ≥20 kPa combined with MELD ≥10 could stratify the risk of mortality and first/further decompensation in ACLD patients. The 2-year mortality and decompensation rates were 36.9% and 61.8%, respectively, in the 305 (18.3%) high-risk patients (with L-SWE ≥20 kPa and MELD ≥10), while in the 944 (56.6%) low-risk patients, these were 1.1% and 3.5%, respectively. Importantly, this M10LS20 algorithm was validated by TE-based LSM and in an additional cohort of 119 patients with valid point shear SWE-LSM.

CONCLUSION

The M10LS20 algorithm allows risk stratification of patients with ACLD. Patients with L-SWE ≥20 kPa and MELD ≥10 should be followed closely and receive intensified care, while patients with low risk may be managed at longer intervals.

Liver Collagen Contents Are Closely Associated with the Severity of Cirrhosis and Posthepatectomy Liver Failure in Patients with Hepatocellular Carcinoma and Child-Pugh Grade A Liver Function

BACKGROUND

Hepatocellular carcinoma (HCC) is usually accompanied by different severities of cirrhosis, which is a risk factor for posthepatectomy liver failure (PHLF). Collagen proportional area (CPA) measurements can quantitatively determine the collagen contents of liver tissue. This study explored the impact of CPA on PHLF, and further investigated the correlation between CPA and a non-invasive method, namely cirrhotic severity scoring (CSS), previously proposed by our team.

METHODS

A total of 224 HCC patients with Child-Pugh grade A liver function undergoing hepatectomy between 2017 and 2019 were retrospectively studied. Quantitative digital image analysis of resected liver tissues was used for the CPA measurement. Risk factors for PHLF were subjected to univariate and multivariate analyses, and the correlation between CPA and CSS was analyzed.

RESULTS

Overall, 28 (12.5%) patients experienced PHLF. Patients with PHLF had higher CPA values than those without PHLF (p < 0.001). Multivariate analysis showed CPA and extent of hepatectomy to be independent risk factors for PHLF. CPA values were divided into four stages based on their quartiles (C1: < 6.6%; C2: 6.6-10.7%; C3: 10.7-18.0%; C4: ≥ 18.0%). The incidence of PHLF increased with increasing CPA stages (p < 0.001). Furthermore, CSS was significantly correlated with CPA (r = 0.720; p < 0.001). The incidence of PHLF also increased with increasing severity of cirrhosis evaluated by CSS (p < 0.001).

CONCLUSIONS

In HCC patients with Child-Pugh grade A liver function, cirrhosis could be staged by liver collagen contents, which significantly influenced PHLF. Furthermore, CSS was useful in the preoperative evaluation of cirrhotic severity.

Comparison of liver biopsies before and after direct-acting antiviral therapy for hepatitis C and correlation with clinical outcome

Direct-acting antivirals (DAA) have replaced interferon (IFN)-based therapies for hepatitis C virus. In this retrospective clinical study, we examined differences in histopathologic features in paired liver biopsies collected from the same patient before and after DAA and correlated these findings with clinical outcome. Biopsies (n = 19) were evaluated by quantitative imaging analysis to measure steatosis and fibrosis. Most patients had decreased steatosis in their post-treatment, follow-up biopsies. However, one patient had a striking increase in steatosis (from 0.86 to 6.32%) and later developed decompensated cirrhosis and hepatocellular carcinoma (HCC). This patient had a marked increase in fibrosis between biopsies, with a CPA of 6.74 to 32.02. Another patient, who already had bridging fibrosis at the time of her pre-treatment biopsy, developed cholangiocarcinoma after DAA. Even though the overall inflammatory activity in the post-treatment biopsies significantly decreased after treatment, 60% of patients had persistent portal lymphocytic inflammation. In summary, DAAs decreased steatosis and hepatic inflammation in most patients, although some may have persistence of lymphocytic portal inflammation. Patients known to have advanced fibrosis at treatment initiation and who have other risk factors for ongoing liver injury, such as steatosis, should be followed closely for the development of adverse outcomes, such as portal hypertension and primary liver cancers.

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.

Diffusion-weighted MRI in staging of post hepatitis C fibrosis: does ADC value challenge liver biopsy?

Background

There is obvious interest in finding a non-invasive diagnostic tool to detect the development of hepatic fibrosis and distinguish between its various stages. Chronic inflammation of the liver secondary to viral hepatitis, autoimmune conditions, sclerosing cholangitis, drug toxicity, chronic alcohol intake, different metabolic disorders, and steatosis lead to fibrosis and maybe cirrhosis. The current study aimed to assess the usefulness of diffusion-weighted magnetic resonance imaging (DW-MRI) in diagnosis of post hepatitis C fibrosis and detection of its stage.

Results

A prospective study had included 232 participants; 120 patients had chronic hepatitis C with/without HCC and 112 subjects had normal liver. There was no significant difference between the two groups regarding age or gender (p 0.192 and 0.227 respectively). DW-MRI was performed using 1.5 T machine. The mean liver ADC values and normalized liver ADC (liver ADC/spleen ADC) were measured at b value 800 s/mm2; both were significantly lower among cases than controls. Cutoff values of liver ADC were 1.531 × 10−3 mm2/s, 1.409 × 10−3 mm2/s, 1.192 × 10−3 mm2/s, and 1.093 × 10−3 mm2/s for METAVIR stages ≥ F1, ≥ F2, ≥ F3, and F4, respectively. Normalized liver ADC showed larger area under the curve (AUC) than mean liver ADC in all differentiation categories except for differentiating between F0 and all other fibrosis stages.

Conclusion

In line with the literature, DW-MR imaging using b value of 800 s/mm2 has proved to be a valuable diagnostic technique for detection and staging of post hepatitis C fibrosis/cirrhosis being noninvasive procedure with acceptable accuracy. DWI using liver/spleen ADC values raised the diagnostic performance with AUC more than 90% in all fibrosis stages on METAVIR score.

Clinical and Molecular Prediction of Hepatocellular Carcinoma Risk

Prediction of hepatocellular carcinoma (HCC) risk becomes increasingly important with recently emerging HCC-predisposing conditions, namely non-alcoholic fatty liver disease and cured hepatitis C virus infection. These etiologies are accompanied with a relatively low HCC incidence rate (~1% per year or less), while affecting a large patient population. Hepatitis B virus infection remains a major HCC risk factor, but a majority of the patients are now on antiviral therapy, which substantially lowers, but does not eliminate, HCC risk. Thus, it is critically important to identify a small subset of patients who have elevated likelihood of developing HCC, to optimize the allocation of limited HCC screening resources to those who need it most and enable cost-effective early HCC diagnosis to prolong patient survival. To date, numerous clinical-variable-based HCC risk scores have been developed for specific clinical contexts defined by liver disease etiology, severity, and other factors. In parallel, various molecular features have been reported as potential HCC risk biomarkers, utilizing both tissue and body-fluid specimens. Deep-learning-based risk modeling is an emerging strategy. Although none of them has been widely incorporated in clinical care of liver disease patients yet, some have been undergoing the process of validation and clinical development. In this review, these risk scores and biomarker candidates are overviewed, and strategic issues in their validation and clinical translation are discussed.

Advances in non-invasive assessment of hepatic fibrosis

Liver fibrosis should be assessed in all individuals with chronic liver disease as it predicts the risk of future liver-related morbidity and thus need for treatment, monitoring and surveillance. Non-invasive fibrosis tests (NITs) overcome many limitations of liver biopsy and are now routinely incorporated into specialist clinical practice. Simple serum-based tests (eg, Fibrosis Score 4, non-alcoholic fatty liver disease Fibrosis Score) consist of readily available biochemical surrogates and clinical risk factors for liver fibrosis (eg, age and sex). These have been extensively validated across a spectrum of chronic liver diseases, however, tend to be less accurate than more 'complex' serum tests, which incorporate direct measures of fibrogenesis or fibrolysis (eg, hyaluronic acid, N-terminal propeptide of type three collagen). Elastography methods quantify liver stiffness as a marker of fibrosis and are more accurate than simple serum NITs, however, suffer increasing rates of unreliability with increasing obesity. MR elastography appears more accurate than sonographic elastography and is not significantly impacted by obesity but is costly with limited availability. NITs are valuable for excluding advanced fibrosis or cirrhosis, however, are not sufficiently predictive when used in isolation. Combining serum and elastography techniques increases diagnostic accuracy and can be used as screening and confirmatory tests, respectively. Unfortunately, NITs have not yet been demonstrated to accurately reflect fibrosis change in response to treatment, limiting their role in disease monitoring. However, recent studies have demonstrated lipidomic, proteomic and gut microbiome profiles as well as microRNA signatures to be promising techniques for fibrosis assessment in the future.

Enhancing the Value of Histopathological Assessment of Allograft Biopsy Monitoring

Traditional histopathological allograft biopsy evaluation provides, within hours, diagnoses, prognostic information, and mechanistic insights into disease processes. However, proponents of an array of alternative monitoring platforms, broadly classified as "invasive" or "noninvasive" depending on whether allograft tissue is needed, question the value proposition of tissue histopathology. The authors explore the pros and cons of current analytical methods relative to the value of traditional and illustrate advancements of next-generation histopathological evaluation of tissue biopsies. We describe the continuing value of traditional histopathological tissue assessment and "next-generation pathology (NGP)," broadly defined as staining/labeling techniques coupled with digital imaging and automated image analysis. Noninvasive imaging and fluid (blood and urine) analyses promote low-risk, global organ assessment, and "molecular" data output, respectively; invasive alternatives promote objective, "mechanistic" insights by creating gene lists with variably increased/decreased expression compared with steady state/baseline. Proponents of alternative approaches contrast their preferred methods with traditional histopathology and: (1) fail to cite the main value of traditional and NGP-retention of spatial and inferred temporal context available for innumerable objective analyses and (2) belie an unfamiliarity with the impact of advances in imaging and software-guided analytics on emerging histopathology practices. Illustrative NGP examples demonstrate the value of multidimensional data that preserve tissue-based spatial and temporal contexts. We outline a path forward for clinical NGP implementation where "software-assisted sign-out" will enable pathologists to conduct objective analyses that can be incorporated into their final reports and improve patient care.

Quantifying and monitoring fibrosis in non-alcoholic fatty liver disease using dual-photon microscopy

OBJECTIVE

Fibrosis stage is strongly associated with liver-related outcomes and is a key surrogate endpoint in drug trials for non-alcoholic steatohepatitis. Dual-photon microscopy allows automated quantification of fibrosis-related parameters (q-FPs) and may facilitate large-scale histological studies. We aim to validate the performance of q-FPs in a large histological cohort.

DESIGN

344 patients with non-alcoholic fatty liver disease (NAFLD) underwent 428 liver biopsies (240 had paired transient elastography examination). Fibrosis stage was scored using the NASH Clinical Research Network system, and q-FPs were measured by dual-photon microscopy using unstained slides. Patients were randomly assigned to the training and validation cohorts to test the performance of individual q-FPs and derive optimal cut-offs.

RESULTS

Over 25 q-FPs had area under the receiver-operating characteristics curves >0.90 for different fibrosis stages. Among them, the perimeter of collagen fibres and number of long collagen fibres had the highest accuracy. At the best cut-offs, the two q-FPs had 88.3%-96.2% sensitivity and 78.1%-91.1% specificity for different fibrosis stages in the validation cohort. q-FPs and histological scoring had nearly identical correlations with liver stiffness measurement, suggesting that the accuracy of q-FPs approached that of histological assessment. Among patients with paired liver biopsies, changes in the same q-FPs were associated with changes in fibrosis stage. At a median follow-up of 5.6 years, baseline q-FPs predicted liver-related events.

CONCLUSION

q-FP is highly accurate in the assessment of fibrosis in NAFLD patients. This automated platform can be used in future studies as objective and reliable evaluation of histological fibrosis.

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.

Multispectral Imaging Enables Characterization of Intrahepatic Macrophages in Patients With Chronic Liver Disease

Intrahepatic macrophages influence the composition of the microenvironment, host immune response to liver injury, and development of fibrosis. Compared with stellate cells, the role of macrophages in the development of fibrosis remains unclear. Multispectral imaging allows detection of multiple markers in situ in human formalin‐fixed, paraffin‐embedded tissue. This cutting‐edge technology is ideal for analyzing human liver tissues, as it allows spectral unmixing of fluorophore signals, subtraction of auto‐fluorescence, and preservation of hepatic architecture. We analyzed five different antibodies commonly observed on macrophage populations (CD68, MAC387, CD163, CD14, and CD16). After optimization of the monoplex stains and development of a Spectral Library, we combined all of the antibodies into a multiplex protocol and used them to stain biopsies collected from representative patients with chronic liver diseases, including chronic hepatitis C, nonalcoholic steatohepatitis, and autoimmune hepatitis. Various imaging modalities were tested, including cell phenotyping, tissue segmentation, t‐distributed stochastic neighbor embedding plots, and phenotype matrices that facilitated comparison and visualization of the identified macrophage and other cellular profiles. We then tested the feasibility of this platform to analyze numerous regions of interest from liver biopsies with multiple patients per group, using batch analysis algorithms. Five populations showed significant differences between patients positive for hepatitis C virus with advanced fibrosis when compared with controls. Three of these were significantly increased in patients with advanced fibrosis when compared to controls, and these included CD163+CD16+, CD68+, and CD68+MAC387+. Conclusion: Spectral imaging microscopy is a powerful tool that enables in situ analysis of macrophages and other cells in human liver biopsies and may lead to more personalized therapeutic approaches in the future.

Quantification of Liver Fibrosis—A Comparative Study

Liver disease has been targeted as the fifth most common cause of death worldwide and tends to steadily rise. In the last three decades, several publications focused on the quantification of liver fibrosis by means of the estimation of the collagen proportional area (CPA) in liver biopsies obtained from digital image analysis (DIA). In this paper, early and recent studies on this topic have been reviewed according to these research aims: the datasets used for the analysis, the employed image processing techniques, the obtained results, and the derived conclusions. The purpose is to identify the major strengths and “gray-areas” in the landscape of this topic.

Quantitative Liver Fibrosis Using Collagen Hybridizing Peptide to Predict Native Liver Survival in Biliary Atresia: A Pilot Study

BACKGROUND/RATIONALE

Biliary atresia (BA) is a cholangiopathy characterized by bile flow obstruction due to destruction of the biliary tree. Without surgical correction with Kasai portoenterostomy (KPE), BA leads to death or liver transplant (LTx). Early-onset, progressive liver fibrosis is a defining characteristic of BA. Collagen hybridizing peptide (CHP) is a synthetic peptide which binds to denatured collagen strands allowing quantification of fibrosis. This technique has not been used on human liver tissue. The aim of this pilot study was to evaluate the utility of CHP as a measurement of quantitative fibrosis to allow earlier survival with native liver prognostication.

RESULTS

We identified 21 patients with wedge liver biopsies available, of which 14 required LTx. No deaths occurred. Patients requiring LTx tended to be girls with a significantly different mean bilirubin (P = 0.002), albumin (P = 0.001), and alanine aminotransferase (P = 0.03) at 3 months post-KPE. By 1 year post-KPE, 50% of patients in the high CHP intensity group required LTx versus 27% in the low CHP. Overall, fibrosis as quantified by CHP at time of KPE was associated with more than 3 times the risk of requiring LTx by 4 years of age (hazard ratio 3.6, 95% confidence interval 1.15-10.93, P = 0.03). When controlling for sex and total bilirubin >2 mg/dL and albumin at 3 months post-KPE, it predicted nearly 7 times the risk of LTx (hazard ratio 6.89, 95% confidence interval 1.38-34.32, P = 0.02).

CONCLUSION

Our results suggest that quantitative assessment of fibrosis at the time of KPE holds promise as an earlier predictor of LTx requirement in BA. A larger study is justified to assess quantitative fibrosis as a BA prognostic tool.

Alcohol-Related Liver Disease Is Rarely Detected at Early Stages Compared With Liver Diseases of Other Etiologies Worldwide

BACKGROUND & AIMS

Despite recent advances in treatment of viral hepatitis, liver-related mortality is high, possibly owing to the large burden of advanced alcohol-related liver disease (ALD). We investigated whether patients with ALD are initially seen at later stages of disease development than patients with hepatitis C virus (HCV) infection or other etiologies.

METHODS

We performed a cross-sectional study of 3453 consecutive patients with either early or advanced liver disease (1699 patients with early and 1754 with advanced liver disease) seen at 17 tertiary care liver or gastrointestinal units worldwide, from August 2015 through March 2017. We collected anthropometric, etiology, and clinical information, as well as and model for end-stage liver disease scores. We used unconditional logistic regression to estimate the odds ratios for evaluation at late stages of the disease progression.

RESULTS

Of the patients analyzed, 81% had 1 etiology of liver disease and 17% had 2 etiologies of liver disease. Of patients seen at early stages for a single etiology, 31% had HCV infection, 21% had hepatitis B virus infection, and 17% had nonalcoholic fatty liver disease, whereas only 3.8% had ALD. In contrast, 29% of patients seen for advanced disease had ALD. Patients with ALD were more likely to be seen at specialized centers, with advanced-stage disease, compared with patients with HCV-associated liver disease (odds ratio, 14.1; 95% CI, 10.5-18.9; P < .001). Of patients with 2 etiologies of liver disease, excess alcohol use was associated with 50% of cases. These patients had significantly more visits to health care providers, with more advanced disease, compared with patients without excess alcohol use. The mean model for end-stage liver disease score for patients with advanced ALD (score, 16) was higher than for patients with advanced liver disease not associated with excess alcohol use (score, 13) (P < .01).

CONCLUSIONS

In a cross-sectional analysis of patients with liver disease worldwide, we found that patients with ALD are seen with more advanced-stage disease than patients with HCV-associated liver disease. Of patients with 2 etiologies of liver disease, excess alcohol use was associated with 50% of cases. Early detection and referral programs are needed for patients with ALD worldwide.

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.

Evaluation of Pancreatic Fibrosis With Acoustic Radiation Force Impulse Imaging and Automated Quantification of Pancreatic Tissue Components

OBJECTIVES

The aim of this study was to determine whether computer-assisted digital analysis and acoustic radiation force impulse (ARFI) imaging were useful for assessing pancreatic fibrosis, and if ARFI imaging predicted postoperative pancreatic fistula (POPF).

METHODS

Seventy-eight patients scheduled to undergo pancreatic resection were enrolled. Shear wave velocity (SWV) at the pancreatic neck was measured preoperatively using ARFI imaging. Pancreatic tissue components on a whole slide image were quantified using an automatic image processing software. The relationship between SWV, fibrotic tissue content, and POPF incidence and clinical severity was analyzed.

RESULTS

The median collagen fiber, fatty tissue, and acinar cell contents were 11.6%, 8.5%, and 61.3%, respectively. Unlike fatty tissue, collagen fiber content and acinar cells were correlated with SWV (ρ = 0.440, P < 0.001 and ρ = -0.428, P < 0.001, respectively). Although collagen fiber content and SWV were associated with the overall incidence of POPF (P = 0.004 and 0.001, respectively), collagen fiber content and SWV had no statistical correlation with clinically relevant POPF (P = 0.268 and 0.052, respectively).

CONCLUSIONS

We objectively quantified the pancreatic tissue components using an automatic image processing software. Shear wave velocity was significantly related to collagen fiber content and suggests that ARFI imaging can be useful for evaluating pancreatic fibrosis.

Advanced septa size quantitation determines the evaluation of histological fibrosis outcome in chronic hepatitis B patients

Hepatitis B (HBV)-related fibrosis can be reversed after effective antiviral therapy. However, detailed changes of collagen characteristics during fibrosis regression remain unclear. Paired biopsy samples obtained from chronic hepatitis B patients were imaged with second harmonic generation/two photon excitation fluorescence (SHG/TPEF)-based microscopy to identify and quantify collagen features in portal, septal, and fibrillar areas. According to the changes of Ishak stage and qFibrosis score, a total of 117 patients with paired liver biopsy appeared to have four different outcomes after 78-week antiviral therapy: fast reverse (9%), reverse (63%), stable (15%), or progress (13%) on fibrosis. Among 71 collagen features identified by SHG/TPEF analysis, the most prominent fibrosis reversion occurred in the "septal" area, followed by the "fibrillar" area, but not in the "portal" area (P < 0.001). Further analysis of 1060 individual septa identified four parameters that correlated with fibrosis reversion: average width, maximum width, number of fibers, and number of cross-link fibers (P < 0.001). Average septal width was independently associated with regressive septa (odds ratio (OR) = 5.22, 95% confidence interval (CI): 4.17-6.53; P < 0.001), with an AUROC of 0.96 (95% CI: 0.95-0.97). The threshold used to discriminate reversal of fibrosis was 30 μm. In conclusion, septal collagen was determined to be the most useful histological feature for evaluation of dynamic changes in liver fibrosis. Septal width was the most predictive indicator of prognosis in liver fibrosis.

Improved performance of quantitative collagen parameters versus standard histology in longitudinal assessment of nonadvanced liver fibrosis for chronic hepatitis B

Monitoring longitudinal nonadvanced fibrosis is a more common scenario in management of chronic hepatitis B (CHB), for which, however, current evaluation methods generally lack sufficient performance. We conducted a proof-of-concept study to evaluate the performance of quantitative fibrous collagen parameters (q-FP) in the assessment. Data sets from a prior CHB trial (NCT00962533) with mostly mild-to-moderate fibrosis participants were used for this study. 301 subjects with paired liver biopsies were consecutively included. Of these, 139 subjects were used to establish the test and the rest for internal validation. Fibrosis change between baseline and week 104 of treatment was blindly assessed with q-FP and was compared with Ishak fibrosis staging. There were 70% and 93% subjects with Ishak F0-2 at baseline and week 104, respectively. For the test of the subjects, q-FP and Ishak staging showed no difference in determining the incidence of fibrosis regression (68% vs 67%; difference = 0.7%, P = 1.00). Q-FP demonstrated that the regression was independently associated with the antiviral efficacy endpoint (OR 3.0, 95% CI 1.4-6.5, P = .005), but Ishak failed the detection (OR 0.6, 95% CI 0.3-1.3, P = .24). Moreover, q-FP directly revealed a higher fibrosis-resistance to antiviral treatment in virus genotypes C vs B and in males vs females. These results were confirmed in the validation subjects. Additionally, a functional model built on the test subjects showed an accuracy of 82% in stratifying fibrosis reversibility of the validation subjects. In conclusion, q-FP could have improved efficiency and accuracy in the longitudinal assessment of mild-to-moderate CHB fibrosis, indicating a potential alternative to current evaluation methodologies.

Risk factors and prevention of hepatocellular carcinoma in the era of precision medicine

Patients who develop chronic fibrotic liver disease, caused by viral or metabolic aetiologies, are at a high risk of developing hepatocellular carcinoma (HCC). Even after complete HCC tumour resection or ablation, the carcinogenic tissue microenvironment in the remnant liver can give rise to recurrent de novo HCC tumours, which progress into incurable, advanced-stage disease in most patients. Thus, early detection and prevention of HCC development is, in principle, the most impactful strategy to improve patient prognosis. However, a "one-size-fits-all" approach to HCC screening for early tumour detection, as recommended by clinical practice guidelines, is utilised in less than 20% of the target population, and the performance of screening modalities, including ultrasound and alpha-fetoprotein, is suboptimal. Furthermore, optimal screening strategies for emerging at-risk patient populations, such as those with chronic hepatitis C after viral cure, or those with non-cirrhotic, non-alcoholic fatty liver disease remain controversial. New HCC biomarkers and imaging modalities may improve the sensitivity and specificity of HCC detection. Clinical and molecular HCC risk scores will enable precise HCC risk prediction followed by tailoured HCC screening of individual patients, maximising cost-effectiveness and optimising allocation of limited medical resources. Several aetiology-specific and generic HCC chemoprevention strategies are evolving. Epidemiological and experimental studies have identified candidate chemoprevention targets and therapies, including statins, anti-diabetic drugs, and selective molecular targeted agents, although their clinical testing has been limited by the lengthy process of cancer development that requires long-term, costly studies. Individual HCC risk prediction is expected to overcome the challenge by enabling personalised chemoprevention, targeting high-risk patients for precision HCC prevention and substantially improving the dismal prognosis of HCC.

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

Accurate staging of liver fibrosis is crucial to guide therapeutic decisions for patients with nonalcoholic fatty liver disease (NAFLD). Digital image analysis has emerged as a promising tool for quantitative assessment of fibrosis in chronic liver diseases. We sought to determine the relationship of histologic fibrosis stage with fiber amounts quantified in liver biopsy specimens for the better understanding of NAFLD progression. We measured area ratios of collagen and elastin fibers in Elastica van Gieson-stained biopsy tissues from 289 patients with NAFLD from four hospitals using an automated computational method and examined their correlations with Brunt's fibrosis stage. As a secondary analysis, we performed multivariable logistic regression analysis to assess the associations of the combined area ratios of collagen and elastin with noninvasive fibrosis markers. The combined fiber area ratios correlated strongly with Brunt's stage (Spearman correlation coefficient, 0.78; P < 0.0001), but this relationship was nonlinear (P = 0.007) with striking differences between stage 4 (median area ratios, 12.3%) and stages 0-3 (2.1%, 2.8%, 4.3%, and 4.8%, respectively). Elastin accumulation was common in areas of thick bridging fibrosis and thickened venous walls but not in areas of perisinusoidal fibrosis. The highest tertile of the combined fiber area ratios was associated with the fibrosis-4 index and serum type IV collagen 7s domain (7s collagen) levels, whereas the upper two tertiles of the fiber amounts significantly associated with body mass index, aspartate aminotransferase, and 7s collagen in the multivariable analysis. Conclusion: Quantitative fibrosis assessment reveals a nonlinear relationship between fibrosis stage and fiber amount, with a marked difference between stage 4 and stage 3 and much smaller differences among stages 0-3, suggesting a heterogeneity in disease severity within NAFLD-related cirrhosis. (Hepatology Communications 2018;2:58-68).

An Inexpensive Digital Image Analysis Technique for Liver Fibrosis Quantification in Chronic Hepatitis B Patients

BACKGROUND AND AIM

Quantitative digital imaging analysis to evaluate liver fibrosis is accurate, but its clinical use is limited by its high cost and lack of standardization. We aimed to validate an inexpensive digital imaging analysis technique for fibrosis quantification in chronic hepatitis B patients.

MATERIAL AND METHODS

In total, 142 chronic hepatitis B patients who underwent liver biopsy and analysis of serum fibrosis markers were included. Images of Sirius red stain sections were captured and processed using Adobe Photoshop CS3 software. The percentage of fibrosis (fibrosis index) was determined by the ratio of the fibrosis area to the total sample area, expressed in pixels, and calculated automatically.

RESULTS

A strong correlation between the fibrosis index and the Ishak, Metavir, and Laennec histological staging systems were observed (r = 0.83, 0.86, and 0.84, respectively; < 0.001). The cutoff value associated with cirrhosis was 7.7% with an area under the receiver operating characteristic curve (AUROC) of 0.95 (95% confidence interval [CI], 0.92-0.99, p < 0.001). Furthermore, the fibrosis index yielded a cutoff value of 8.9% (AUROC, 0.74; 95% CI, 0.66-0.86), 12% (AUROC, 0.84; 95% CI, 0.75-0.93), and 14% (AUROC, 0.97; 95% CI, 0.92-1.0) for the diagnosis of cirrhosis 4a, 4b, and 4c, respectively. No serum markers or fibrosis models were correlated with the fibrosis index in Metavir F2-F4.

CONCLUSIONS

The present digital imaging analysis technique is reproducible and available worldwide, allowing its use in clinical practice, and can be considered as a complementary tool to traditional histological methods.

Interobserver Variability in Histologic Evaluation of Liver Fibrosis Using Categorical and Quantitative Scores

Objectives

The aim of the study was to investigate the interobserver agreement for categorical and quantitative scores of liver fibrosis.

Methods

Sixty-five consecutive biopsy specimens from patients with mixed liver disease etiologies were assessed by three pathologists using the Ishak and nonalcoholic steatohepatitis Clinical Research Network (NASH CRN) scoring systems, and the fibrosis area (collagen proportionate area [CPA]) was estimated by visual inspection (visual-CPA). A subset of 20 biopsy specimens was analyzed using digital imaging analysis (DIA) for the measurement of CPA (DIA-CPA).

Results

The bivariate weighted κ between any two pathologists ranged from 0.57 to 0.67 for Ishak staging and from 0.47 to 0.57 for the NASH CRN staging. Bland-Altman analysis showed poor agreement between all possible pathologist pairings for visual-CPA but good agreement between all pathologist pairings for DIA-CPA. There was good agreement between the two pathologists who assessed biopsy specimens by visual-CPA and DIA-CPA. The intraclass correlation coefficient, which is equivalent to the κ statistic for continuous variables, was 0.78 for visual-CPA and 0.97 for DIA-CPA.

Conclusions

These results suggest that DIA-CPA is the most robust method for assessing liver fibrosis followed by visual-CPA. Categorical scores perform less well than both the quantitative CPA scores assessed here.

A methodology for automated CPA extraction using liver biopsy image analysis and machine learning techniques

BACKGROUND AND OBJECTIVE

Collagen proportional area (CPA) extraction in liver biopsy images provides the degree of fibrosis expansion in liver tissue, which is the most characteristic histological alteration in hepatitis C virus (HCV). Assessment of the fibrotic tissue is currently based on semiquantitative staging scores such as Ishak and Metavir. Since its introduction as a fibrotic tissue assessment technique, CPA calculation based on image analysis techniques has proven to be more accurate than semiquantitative scores. However, CPA has yet to reach everyday clinical practice, since the lack of standardized and robust methods for computerized image analysis for CPA assessment have proven to be a major limitation.

METHODS

The current work introduces a three-stage fully automated methodology for CPA extraction based on machine learning techniques. Specifically, clustering algorithms have been employed for background-tissue separation, as well as for fibrosis detection in liver tissue regions, in the first and the third stage of the methodology, respectively. Due to the existence of several types of tissue regions in the image (such as blood clots, muscle tissue, structural collagen, etc.), classification algorithms have been employed to identify liver tissue regions and exclude all other non-liver tissue regions from CPA computation.

RESULTS

For the evaluation of the methodology, 79 liver biopsy images have been employed, obtaining 1.31% mean absolute CPA error, with 0.923 concordance correlation coefficient.

CONCLUSIONS

The proposed methodology is designed to (i) avoid manual threshold-based and region selection processes, widely used in similar approaches presented in the literature, and (ii) minimize CPA calculation time.

Metavir and FIB-4 scores are associated with patient prognosis after curative hepatectomy in hepatitis B virus-related hepatocellular carcinoma: a retrospective cohort study at two centers in China

Although Metavir and Fibrosis-4 (FIB-4) scores are typically used to assess the severity of liver fibrosis, the relationship between these scores and patient outcome in hepatocellular carcinoma (HCC) is unclear. The aim of this study was to evaluate the prognostic value of the severity of hepatic fibrosis in HBV-related HCC patients after curative resection. We examined the prognostic roles of the Metavir and preoperative FIB-4 scores in 432 HBV-HCC patients who underwent curative resection at two different medical centers located in western (Chongqing) and eastern (Shanghai) China. In the testing set (n = 108), the Metavir, FIB-4, and combined Metavir/FIB-4 scores were predictive of overall survival (OS) and recurrence-free survival (RFS). Additionally, they were associated with several clinicopathologic variables. In the validation set (n = 324), the Metavir, FIB-4, and combined Metavir/FIB-4 scores were associated with poor prognosis in HCC patients after curative resection. Importantly, in the negative alpha-fetoprotein subgroup (≤ 20 ng/mL), the FIB-4 index (I vs. II) could discriminate between patient outcomes (high or low OS and RFS). Thus Metavir, preoperative FIB-4, and combined Metavir/FIB-4 scores are prognostic markers in HBV-HCC patients after curative hepatectomy.

Antifibrotics in chronic liver disease: tractable targets and translational challenges

Chronic liver disease prevalence is increasing globally. Iterative liver damage, secondary to any cause of liver injury, results in progressive fibrosis, disrupted hepatic architecture, and aberrant regeneration, which are defining characteristics of liver cirrhosis. Liver transplantation is an effective treatment for end-stage liver disease; however, demand greatly outweighs donor organ supply, and in many parts of the world liver transplantation is unavailable. Hence, effective antifibrotic therapies are urgently required. In the past decade, rapid progress has been made in our understanding of the pathophysiology of liver fibrosis and a large number of potential cellular and molecular antifibrotic targets have been identified. This has led to numerous clinical trials of antifibrotic agents in patients with chronic liver disease. However, none of these have resulted in a robust and reproducible effect on fibrosis. It is therefore imperative that the ongoing translational challenges are addressed, to convert scientific discoveries into potent antifibrotics and enable bridging of the translational gap between putative therapeutic targets and effective treatments for patients with chronic liver disease.

A clustering based method for collagen proportional area extraction in liver biopsy images

Collagen Proportional Area (CPA) extraction using digital image analysis (DIA) in liver biopsies provides an effective way to estimate the liver disease staging. CPA represents accurately fibrosis expansion in liver tissue. This paper presents an automated clustering-based method for fibrosis detection and CPA computation. Initially, a k-means based approach is employed to detect the liver tissue and eliminate the background. Next, the method decides about the adequacy of current biopsy, according to the size of liver tissue. Biopsies which contain small and segmented specimens must be repeated. Since the tissue has been detected, fibrosis areas are also found in the tissue. Finally, CPA is computed. For the evaluation of the proposed method 25 images are employed and the percentage errors of CPA are computed for each image. In the majority of the cases, small variation of CPA is computed, comparing to the expert's annotation.

Evaluation of liver fibrosis: "Something old, something new…"

Hepatic fibrogenesis may gradually result to cirrhosis due to the accumulation of extracellular matrix components as a response to liver injury. Thus, therapeutic decisions in chronic liver disease, regardless of the cause, should first and foremost be guided by an accurate quantification of hepatic fibrosis. Detection and assessment of the extent of hepatic fibrosis represent a challenge in modern Hepatology. Although traditional histological staging systems remain the “best standard”, they are not able to quantify liver fibrosis as a dynamic process and may not accurately substage cirrhosis. This review aims to compare the currently used non-invasive methods of measuring liver fibrosis and provide an update in current tissue-based digital techniques developed for this purpose, that may prove of value in daily clinical practice.

Quantitative fibrosis estimation by image analysis predicts development of decompensation, composite events and defines event-free survival in chronic hepatitis B patients

The extent of fibrosis is a major determinant of the clinical outcome in patients with chronic liver diseases. We undertook this study to explore the degree of fibrosis in baseline liver biopsies to predict clinical outcomes in chronic hepatitis B (CHB) patients. Fibrosis quantification was done by image analysis on Masson's trichrome-stained sections and correlated with clinical and biochemical parameters, liver stiffness and hepatic vein pressure gradient (n = 96). Follow-up information collected related to clinical outcome. A total of 964 cases was analyzed. Median quantitative fibrosis (QF) was 3.7% (interquartile range, 1.6%-9.7%) with substantial variation in various stages. Median QF was F0, 1% (0.7%-1.65%); F1, 3.03% (2.07%-4.0%); F2, 7.1% (5.6%-8.7%); F3, 12.7% (10.15%-16.7%); F4, 26.9% (20.3%-36.4%). QF positively correlated with METAVIR staging, liver stiffness measurement, and hepatic vein pressure gradient. Eighty-nine cases developed liver-related events: decompensation, hepatocellular carcinoma, liver transplantation and death. Cox regression analysis after adjusting for METAVIR staging-QF, albumin, and AST for composite events; QF and albumin for decompensation; and only QF for hepatocellular carcinoma-were found to be significant predictors of clinical outcomes. QF categorized into five stages: QF1, 0%-5%; QF2, 5.1%-10%; QF3, 10.1%-15%; QF4, 15.1%-20%; QF5, >20.1%. In patients with advanced stages of QF, probability of event-free survival found to be low. Quantitative fibrosis in baseline liver biopsy predicts progression of the disease and disease outcome in CHB patients. QF defines the probability of event-free survival in CHB cases.

Elastin Fiber Accumulation in Liver Correlates with the Development of Hepatocellular Carcinoma

Background & Aims

The fibrosis stage, which is evaluated by the distribution pattern of collagen fibers, is a major predictor for the development of hepatocellular carcinoma (HCC) for patients with hepatitis C. Meanwhile, the role of elastin fibers has not yet been elucidated. The present study was conducted to determine the significance of quantifying both collagen and elastin fibers.

Methods

We enrolled 189 consecutive patients with hepatitis C and advanced fibrosis. Using Elastica van Gieson-stained whole-slide images of pretreatment liver biopsies, collagen and elastin fibers were evaluated pixel by pixel (0.46 μm/pixel) using an automated computational method. Consequently, fiber amount and cumulative incidences of HCC within 3 years were analyzed.

Results

There was a significant correlation between collagen and elastin fibers, whereas variation in elastin fiber was greater than in collagen fiber. Both collagen fiber (p = 0.008) and elastin fiber (p < 0.001) were significantly correlated with F stage. In total, 30 patients developed HCC during follow-up. Patients who have higher elastin fiber (p = 0.002) in addition to higher collagen fiber (p = 0.05) showed significantly higher incidences of HCC. With regard to elastin fiber, this difference remained significant in F3 patients. Furthermore, for patients with a higher collagen fiber amount, higher elastin was a significant predictor for HCC development (p = 0.02).

Conclusions

Computational analysis is a novel technique for quantification of fibers with the added value of conventional staging. Elastin fiber is a predictor for the development of HCC independently of collagen fiber and F stage.

Longitudinal assessment of hepatitis C fibrosis progression by collagen and smooth muscle actin morphometry in comparison to serum markers

BACKGROUND

Assessment of fibrosis progression in chronic liver disease relies upon non-invasive tools and changes in semi-quantitative histopathology scores that may not be reliable.

AIM

To assess the diagnostic performance of the FibroSURE (FS) index and collagen/alpha smooth muscle actin (α-SMA) morphometry in relation to longitudinal changes in fibrosis on paired biopsies.

METHODS

The study cohort included 201 chronic hepatitis C (CHC) nonresponders enrolled in a prior phase II anti-fibrotic study. Serum FS and paired biopsies, with both collagen and α-SMA morphometry, were evaluated at baseline and week 52.

RESULTS

Study patients were mostly male (67%) and Caucasian (77%), with Ishak stages 2 (n = 79), 3 (n = 88) and 4 (n = 30), excluded (n = 4 stage 1 or 5). Mean biopsy length was 22.9 mm. For baseline Ishak 2/3 vs. 4, there were no significant differences in AUROCs for collagen (0.71), SMA (0.66) or FS (0.70). At week 52, 62% of patients had no change in Ishak stage, but collagen/α-SMA increased by 34-51% (P < 0.0001), and FS decreased by 5% (P = 0.008). Among the 33% of patients with +/-1 Ishak stage change, FS changes were not significant, but α-SMA increased 29-72%, and collagen increased by 12-38% (P = 0.01 for +1 only).

CONCLUSIONS

Longitudinal changes in collagen and α-SMA morphometry are apparent prior to change in histological stage or FibroSURE in CHC nonresponders with intermediate fibrosis. This likely reflects quantitative morphological differences that are not detected by routine histological staging or serum markers such as FibroSURE.

Transient and 2-Dimensional Shear-Wave Elastography Provide Comparable Assessment of Alcoholic Liver Fibrosis and Cirrhosis

BACKGROUND & AIMS

Alcohol abuse causes half of all deaths from cirrhosis in the West, but few tools are available for noninvasive diagnosis of alcoholic liver disease. We evaluated 2 elastography techniques for diagnosis of alcoholic fibrosis and cirrhosis; liver biopsy with Ishak score and collagen-proportionate area were used as reference.

METHODS

We performed a prospective study of 199 consecutive patients with ongoing or prior alcohol abuse, but without known liver disease. One group of patients had a high pretest probability of cirrhosis because they were identified at hospital liver clinics (in Southern Denmark). The second, lower-risk group, was recruited from municipal alcohol rehabilitation centers and the Danish national public health portal. All subjects underwent same-day transient elastography (FibroScan), 2-dimensional shear wave elastography (Supersonic Aixplorer), and liver biopsy after an overnight fast.

RESULTS

Transient elastography and 2-dimensional shear wave elastography identified subjects in each group with significant fibrosis (Ishak score ≥3) and cirrhosis (Ishak score ≥5) with high accuracy (area under the curve ≥0.92). There was no difference in diagnostic accuracy between techniques. The cutoff values for optimal identification of significant fibrosis by transient elastography and 2-dimensional shear wave elastography were 9.6 kPa and 10.2 kPa, and for cirrhosis 19.7 kPa and 16.4 kPa. Negative predictive values were high for both groups, but the positive predictive value for cirrhosis was >66% in the high-risk group vs approximately 50% in the low-risk group. Evidence of alcohol-induced damage to cholangiocytes, but not ongoing alcohol abuse, affected liver stiffness. The collagen-proportionate area correlated with Ishak grades and accurately identified individuals with significant fibrosis and cirrhosis.

CONCLUSIONS

In a prospective study of individuals at risk for liver fibrosis due to alcohol consumption, we found elastography to be an excellent tool for diagnosing liver fibrosis and for excluding (ruling out rather than ruling in) cirrhosis.