Automated evaluation of liver fibrosis in thioacetamide, carbon tetrachloride, and bile duct ligation rodent models using second-harmonic generation/two-photon excited fluorescence microscopy

The Emerging Role of Second Harmonic Generation/Two Photon Excitation for Precision Digital Analysis of Liver Fibrosis in MASH Clinical Trials

Conventional histopathological evaluation of liver biopsy slides has been invaluable in assessing the causes of liver injury, the severity of the underlying disease processes, and the degree of resulting fibrosis. However, the use of conventional histologic assessments as endpoints in clinical trials is limited by the reliability of scoring systems, variability in interpretation of histologic features and translation of continuous variables into categorical scores. To increase the precision and reproducibility of liver biopsy assessment, several artificial intelligence/machine learning (AI/ML) approaches have been developed to analyse high resolution digital images of liver biopsy specimens. Multiple AI/ML platforms are in development with promising results in post-hoc analyses of clinical trial biopsies. One such technique employs images generated by Second Harmonic Generation/Two Photon Excitation (SHG/TPE) microscopy that uniquely uses unstained liver biopsies to provide high resolution images of collagen fibres to assess and quantify collagen morphometry, and avoid challenges related to staining variability. One SHG/TPE microscopy methodology coupled with AI/ML based analysis, qFibrosis™, has been used post-hoc as an exploratory endpoint in several clinical trials for metabolic dysfunction-associated steatohepatitis (MASH) demonstrating its ability to provide a consistent and more nuanced assessment of liver fibrosis that still correlates well with traditional staging. This review summarizes the development of qFibrosis and outlines the need for additional studies to validate it as a sensitive marker for changes in fibrosis in the context of treatment trials and correlate these changes with subsequent liver-related outcomes.

Toward cancer detection by label-free microscopic imaging in oncological surgery: Techniques, instrumentation and applications

This review examines the clinical application of label-free microscopy and spectroscopy, which are based on optical signals emitted by tissue components. Over the past three decades, a variety of techniques have been investigated with the aim of developing an in situ histopathology method that can rapidly and accurately identify tumor margins during surgical procedures. These techniques can be divided into two groups. One group encompasses techniques exploiting linear optical signals, and includes infrared and Raman microspectroscopy, and autofluorescence microscopy. The second group includes techniques based on nonlinear optical signals, including harmonic generation, coherent Raman scattering, and multiphoton autofluorescence microscopy. Some of these methods provide comparable information, while others are complementary. However, all of them have distinct advantages and disadvantages due to their inherent nature. The first part of the review provides an explanation of the underlying physics of the excitation mechanisms and a description of the instrumentation. It also covers endomicroscopy and data analysis, which are important for understanding the current limitations in implementing label-free techniques in clinical settings. The second part of the review describes the application of label-free microscopy imaging to improve oncological surgery with focus on brain tumors and selected gastrointestinal cancers, and provides a critical assessment of the current state of translation of these methods into clinical practice. Finally, the potential of confocal laser endomicroscopy for the acquisition of autofluorescence is discussed in the context of immediate clinical applications.

A novel 11β-HSD1 inhibitor ameliorates liver fibrosis by inhibiting the notch signaling pathway and increasing NK cell population

11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) regulates hepatic glucose output and is implicated in liver fibrosis. We aimed to investigate the anti-fibrotic effect of a novel 11β-HSD1 inhibitor in a thioacetamide (TAA)-induced liver fibrosis mouse model. Mice were administered TAA for 19 weeks and treated with 11β-HSD1 inhibitor for the last 9 weeks. Treatment with 11β-HSD1 inhibitor significantly reduced fibrosis area, alanine aminotransferase, and aspartate aminotransferase levels compared to the TAA-only group. Inhibition of 11β-HSD1 led to a decrease in intracellular cortisol levels, which suppressed the activation of hepatic stellate cells. RNA sequencing revealed significant downregulation of the Notch signaling pathway, including reduced expression of Notch ligands and receptors, as well as downstream genes. Furthermore, 11β-HSD1 inhibition enhanced NK cell-mediated immune responses, as indicated by the upregulation of NK cell-related genes and increased NK cell populations confirmed by mass cytometry. This increase in NK cell activity contributed to the clearance of activated HSCs and the attenuation of fibrosis. These findings suggest that 11β-HSD1 inhibition alleviates liver fibrosis through Notch pathway suppression and enhancement of NK cell-mediated immune responses. Our results support the therapeutic potential of a novel 11β-HSD1 inhibitor for treating liver fibrosis.

Quantitative fibrosis identifies biliary tract involvement and is associated with outcomes in pediatric autoimmune liver disease

BACKGROUND

Children with autoimmune liver disease (AILD) may develop fibrosis-related complications necessitating a liver transplant. We hypothesize that tissue-based analysis of liver fibrosis by second harmonic generation (SHG) microscopy with artificial intelligence analysis can yield prognostic biomarkers in AILD.

METHODS

Patients from single-center studies with unstained slides from clinically obtained liver biopsies at AILD diagnosis were identified. Baseline demographics and liver biochemistries at diagnosis and 1 year were collected. Clinical endpoints studied included the presence of varices, variceal bleeding, ascites, HE, and liver transplant. In collaboration with HistoIndex, unstained slides underwent SHG/artificial intelligence analysis to map fibrosis according to 10 quantitative fibrosis parameters based on tissue location, including total, periportal, perisinusoidal, and pericentral area and length of strings.

RESULTS

Sixty-three patients with AIH (51%), primary sclerosing cholangitis (30%), or autoimmune sclerosing cholangitis (19%) at a median of 14 years old (range: 3-24) were included. An unsupervised analysis of quantitative fibrosis parameters representing total and portal fibrosis identified a patient cluster with more primary sclerosing cholangitis/autoimmune sclerosing cholangitis. This group had more fibrosis at diagnosis by METAVIR classification of histopathological review of biopsies (2.5 vs. 2; p = 0.006). This quantitative fibrosis pattern also predicted abnormal 12-month ALT with an OR of 3.6 (1.3-10, p = 0.014), liver complications with an HR of 3.2 (1.3-7.9, p = 0.01), and liver transplantation with an HR of 20.1 (3-135.7, p = 0.002).

CONCLUSIONS

The application of SHG/artificial intelligence algorithms in pediatric-onset AILD provides improved insight into liver histopathology through fibrosis mapping. SHG allows objective identification of patients with biliary tract involvement, which may be associated with a higher risk for refractory disease.

Hepatic Steatosis Analysis in Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Artificial Intelligence

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by the accumulation of fat in the liver, excluding excessive alcohol consumption and other known causes of liver injury. Animal models are often used to explore different pathogenic mechanisms and therapeutic targets of MASLD. The aim of this study is to apply an artificial intelligence (AI) system based on second-harmonic generation (SHG)/two-photon-excited fluorescence (TPEF) technology to automatically assess the dynamic patterns of hepatic steatosis in MASLD mouse models.

METHODS

We evaluated the characteristics of hepatic steatosis in mouse models of MASLD using AI analysis based on SHG/TPEF images. Six different models of MASLD were induced in C57BL/6 mice by feeding with a western or high-fat diet, with or without fructose in their drinking water, and/or by weekly injections of carbon tetrachloride.

RESULTS

Body weight, serum lipids, and liver enzyme markers increased at 8 and 16 weeks in each model compared to baseline. Steatosis grade showed a steady upward trend. However, the non-alcoholic steatohepatitis (NASH) Clinical Research Network (CRN) histological scoring method detected no significant difference between 8 and 16 weeks. In contrast, AI analysis was able to quantify dynamic changes in the area, number, and size of hepatic steatosis automatically and objectively, making it more suitable for preclinical MASLD animal experiments.

CONCLUSIONS

AI recognition technology may be a new tool for the accurate diagnosis of steatosis in MASLD, providing a more precise and objective method for evaluating steatosis in preclinical murine MASLD models under various experimental and treatment conditions.

The galectin-3 inhibitor selvigaltin reduces liver inflammation and fibrosis in a high fat diet rabbit model of metabolic-associated steatohepatitis

Introduction

Galectin-3 is a pro-fibrotic β-galactoside binding lectin highly expressed in fibrotic liver and implicated in hepatic fibrosis. Selvigaltin (previously known as GB1211) is a novel orally active galectin-3 small molecule inhibitor that has high affinity for galectin-3 (human KD = 25 nM; rabbit KD = 12 nM) and high oral bioavailability in rabbits and man. In this study the efficacy of selvigaltin was investigated in a high fat diet (HFD) rabbit model of metabolic-associated steatohepatitis (MASH).

Methods

Male New Zealand White rabbits were individually caged under standard conditions in a temperature and humidity-controlled room on a 12 h light/darkness cycle. After 1 week of regular diet (RD), rabbits were randomly assigned for 8 or 12 weeks to different groups: RD/vehicle, RD/selvigaltin, HFD (8 weeks), HFD/vehicle and HFD/selvigaltin (0.3, 1.0, 5.0 or 30 mg/kg selvigaltin with vehicle/selvigaltin p.o. dosed therapeutically q.d. 5 days per week from week 9 or 12). Liver inflammation, steatosis, ballooning, and fibrosis was measured via blood metabolic markers, histomorphological evaluation [Oil Red O, Giemsa, Masson's trichome, picrosirius red (PSR) and second harmonic generation (SHG)], and mRNA and protein expression.

Results

Steatosis, inflammation, ballooning, and fibrosis were all increased from RD to HFD/vehicle groups. Selvigaltin demonstrated target engagement by significantly decreasing galectin-3 levels in the liver as measured via immunohistochemistry and mRNA analysis. Selvigaltin dose-dependently reduced biomarkers of liver function (AST, ALT, bilirubin), inflammation (cells foci), and fibrosis (PSR, SHG), as well as decreasing the mRNA and protein expression of several key inflammation and fibrosis biomarkers (e.g., IL6, TGFβ3, SNAI2, collagen). Doses of 1.0 or 5.0 mg/kg demonstrated consistent efficacy across most biological endpoints supporting the current clinical doses of selvigaltin being investigated in liver disease.

Discussion

Selvigaltin significantly reduced hepatic inflammation and fibrosis in an HFD rabbit model of MASH following therapeutic dosing for 4 weeks in a dose-dependent manner. These data support the human selvigaltin dose of 100 mg b.i.d. that has been shown to reduce key liver biomarkers during a clinical study in liver cirrhosis.

Hepatoprotective effects of paeonol by suppressing hepatic stellate cell activation via inhibition of SMAD2/3 and STAT3 pathways

Hepatic stellate cell (HSC) activation is a key event in extracellular matrix accumulation, causing hepatic fibrosis. Therefore, identifying chemicals that inhibit HSC activation is an important therapeutic strategy for hepatic fibrosis. The aim of this study was to investigate the therapeutic effects of paeonol on HSC activation. In LX-2 cells, paeonol inhibited the expression of collagen and decreased the expression of HSC activation markers. In mice with thioacetamide-induced liver fibrosis, paeonol treatment decreased the serum levels of aspartate aminotransferase and alanine transaminase and mRNA expression of α-smooth muscle actin, platelet-derived growth factor-β, and connective-tissue growth factor. Investigation of the underlying molecular mechanism of paeonol showed that paeonol inhibits the SMAD2/3 and STAT3 signaling pathways that are important for HSC activation. On the basis of these results, paeonol should be investigated and developed further for hepatic fibrosis treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10068-023-01440-9.

Artificial intelligence-assisted digital pathology for non-alcoholic steatohepatitis: current status and future directions

The worldwide prevalence of non-alcoholic steatohepatitis (NASH) is increasing, causing a significant medical burden, but no approved therapeutics are currently available. NASH drug development requires histological analysis of liver biopsies by expert pathologists for trial enrolment and efficacy assessment, which can be hindered by multiple issues including sample heterogeneity, inter-reader and intra-reader variability, and ordinal scoring systems. Consequently, there is a high unmet need for accurate, reproducible, quantitative, and automated methods to assist pathologists with histological analysis to improve the precision around treatment and efficacy assessment. Digital pathology (DP) workflows in combination with artificial intelligence (AI) have been established in other areas of medicine and are being actively investigated in NASH to assist pathologists in the evaluation and scoring of NASH histology. DP/AI models can be used to automatically detect, localise, quantify, and score histological parameters and have the potential to reduce the impact of scoring variability in NASH clinical trials. This narrative review provides an overview of DP/AI tools in development for NASH, highlights key regulatory considerations, and discusses how these advances may impact the future of NASH clinical management and drug development. This should be a high priority in the NASH field, particularly to improve the development of safe and effective therapeutics.

Automated quantitative assay of fibrosis characteristics in tuberculosis granulomas

Introduction

Granulomas, the pathological hallmark of Mycobacterium tuberculosis (Mtb) infection, are formed by different cell populations. Across various stages of tuberculosis conditions, most granulomas are classical caseous granulomas. They are composed of a necrotic center surrounded by multilayers of histocytes, with the outermost layer encircled by fibrosis. Although fibrosis characterizes the architecture of granulomas, little is known about the detailed parameters of fibrosis during this process.

Methods

In this study, samples were collected from patients with tuberculosis (spanning 16 organ types), and Mtb-infected marmosets and fibrotic collagen were characterized by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy using a stain-free, fully automated analysis program.

Results

Histopathological examination revealed that most granulomas share common features, including necrosis, solitary and compact structure, and especially the presence of multinuclear giant cells. Masson's trichrome staining showed that different granuloma types have varying degrees of fibrosis. SHG imaging uncovered a higher proportion (4%~13%) of aggregated collagens than of disseminated type collagens (2%~5%) in granulomas from matched tissues. Furthermore, most of the aggregated collagen presented as short and thick clusters (200~620 µm), unlike the long and thick (200~300 µm) disseminated collagens within the matched tissues. Matrix metalloproteinase-9, which is involved in fibrosis and granuloma formation, was strongly expressed in the granulomas in different tissues.

Discussion

Our data illustrated that different tuberculosis granulomas have some degree of fibrosis in which collagen strings are short and thick. Moreover, this study revealed that the SHG imaging program could contribute to uncovering the fibrosis characteristics of tuberculosis granulomas.

Collagen co-localized with macrovesicular steatosis better differentiates fibrosis progression in non-alcoholic fatty liver disease mouse models

Background

Non-alcoholic fatty liver disease (NAFLD) is a global commonly occurring liver disease. However, its exact pathogenesis is not fully understood. The purpose of this study was to quantitatively evaluate the progression of steatosis and fibrosis by examining their distribution, morphology, and co-localization in NAFLD animal models.

Methods

Six mouse NAFLD groups were established: (1) western diet (WD) group; (2) WD with fructose in drinking water (WDF) group; (3) WDF + carbon tetrachloride (CCl4) group, WDF plus intraperitoneal injection of CCl4; (4) high-fat diet (HFD) group, (5) HFD with fructose (HFDF) group; and (6) HFDF + CCl4 group, HFDF plus intraperitoneal injection of CCl4. Liver tissue specimens from NAFLD model mice were collected at different time points. All the tissues were serially sectioned for histological staining and second-harmonic generation (SHG)/two-photon excitation fluorescence imaging (TPEF) imaging. The progression of steatosis and fibrosis was analyzed using SHG/TPEF quantitative parameters with respect to the non-alcoholic steatohepatitis Clinical Research Network scoring system.

Results

qSteatosis showed a good correlation with steatosis grade (R: 0.823-0.953, p < 0.05) and demonstrated high performance (area under the curve [AUC]: 0.617-1) in six mouse models. Based on their high correlation with histological scoring, qFibrosis containing four shared parameters (#LongStrPS, #ThinStrPS, #ThinStrPSAgg, and #LongStrPSDis) were selected to create a linear model that could accurately identify differences among fibrosis stages (AUC: 0.725-1). qFibrosis co-localized with macrosteatosis generally correlated better with histological scoring and had a higher AUC in six animal models (AUC: 0.846-1).

Conclusion

Quantitative assessment using SHG/TPEF technology can be used to monitor different types of steatosis and fibrosis progression in NAFLD models. The collagen co-localized with macrosteatosis could better differentiate fibrosis progression and might aid in developing a more reliable and translatable fibrosis evaluation tool for animal models of NAFLD.

Quantitative image-based collagen structural features predict the reversibility of hepatitis C virus-induced liver fibrosis post antiviral therapies

The novel targeted therapeutics for hepatitis C virus (HCV) in last decade solved most of the clinical needs for this disease. However, despite antiviral therapies resulting in sustained virologic response (SVR), a challenge remains where the stage of liver fibrosis in some patients remains unchanged or even worsens, with a higher risk of cirrhosis, known as the irreversible group. In this study, we provided novel tissue level collagen structural insight into early prediction of irreversible cases via image based computational analysis with a paired data cohort (of pre- and post-SVR) following direct-acting-antiviral (DAA)-based treatment. Two Photon Excitation and Second Harmonic Generation microscopy was used to image paired biopsies from 57 HCV patients and a fully automated digital collagen profiling platform was developed. In total, 41 digital image-based features were profiled where four key features were discovered to be strongly associated with fibrosis reversibility. The data was validated for prognostic value by prototyping predictive models based on two selected features: Collagen Area Ratio and Collagen Fiber Straightness. We concluded that collagen aggregation pattern and collagen thickness are strong indicators of liver fibrosis reversibility. These findings provide the potential implications of collagen structural features from DAA-based treatment and paves the way for a more comprehensive early prediction of reversibility using pre-SVR biopsy samples to enhance timely medical interventions and therapeutic strategies. Our findings on DAA-based treatment further contribute to the understanding of underline governing mechanism and knowledge base of structural morphology in which the future non-invasive prediction solution can be built upon.

Label-free multiphoton microscopy enables histopathological assessment of colorectal liver metastases and supports automated classification of neoplastic tissue

As the state of resection margins is an important prognostic factor after extirpation of colorectal liver metastases, surgeons aim to obtain negative margins, sometimes elaborated by resections of the positive resection plane after intraoperative frozen sections. However, this is time consuming and results sometimes remain unclear during surgery. Label-free multimodal multiphoton microscopy (MPM) is an optical technique that retrieves morpho-chemical information avoiding all staining and that can potentially be performed in real-time. Here, we investigated colorectal liver metastases and hepatic tissue using a combination of three endogenous nonlinear signals, namely: coherent anti-Stokes Raman scattering (CARS) to visualize lipids, two-photon excited fluorescence (TPEF) to visualize cellular patterns, and second harmonic generation (SHG) to visualize collagen fibers. We acquired and analyzed over forty thousand MPM images of metastatic and normal liver tissue of 106 patients. The morphological information with biochemical specificity produced by MPM allowed discriminating normal liver from metastatic tissue and discerning the tumor borders on cryosections as well as formalin-fixed bulk tissue. Furthermore, automated tissue type classification with a correct rate close to 95% was possible using a simple approach based on discriminant analysis of texture parameters. Therefore, MPM has the potential to increase the precision of resection margins in hepatic surgery of metastases without prolonging surgical intervention.

Automated whole slide image analysis for a translational quantification of liver fibrosis

Current literature highlights the need for precise histological quantitative assessment of fibrosis which cannot be achieved by conventional scoring systems, inherent to their discontinuous values and reader-dependent variability. Here we used an automated image analysis software to measure fibrosis deposition in two relevant preclinical models of liver fibrosis, and established correlation with other quantitative fibrosis descriptors. Longitudinal quantification of liver fibrosis was carried out during progression of post-necrotic (CCl₄-induced) and metabolic (HF-CDAA feeding) models of chronic liver disease in mice. Whole slide images of picrosirius red-stained liver sections were analyzed using a fully automated, unsupervised software. Fibrosis was characterized by a significant increase of collagen proportionate area (CPA) at weeks 3 (CCl₄) and 8 (HF-CDAA) with a progressive increase up to week 18 and 24, respectively. CPA was compared to collagen content assessed biochemically by hydroxyproline assay (HYP) and by standard histological staging systems. CPA showed a high correlation with HYP content for CCl₄ (r = 0.8268) and HF-CDAA (r = 0.6799) models. High correlations were also found with Ishak score or its modified version (r = 0.9705) for CCl₄ and HF-CDAA (r = 0.9062) as well as with NASH CRN for HF-CDAA (r = 0.7937). Such correlations support the use of automated digital analysis as a reliable tool to evaluate the dynamics of liver fibrosis and efficacy of antifibrotic drug candidates in preclinical models.

Mass Cytometry Study on Hepatic Fibrosis and Its Drug-Induced Recovery Using Mouse Peripheral Blood Mononuclear Cells

The number of patients with liver diseases has increased significantly with the progress of global industrialization. Hepatic fibrosis, one of the most common liver diseases diagnosed in many developed countries, occurs in response to chronic liver injury and is primarily driven by the development of inflammation. Earlier immunological studies have been focused on the importance of the innate immune response in the pathophysiology of steatohepatitis and fibrosis, but recently, it has also been reported that adaptive immunity, particularly B cells, plays an essential role in hepatic inflammation and fibrosis. However, despite recent data showing the importance of adaptive immunity, relatively little is known about the role of B cells in the pathogenesis of steatohepatitis fibrosis. In this study, a single-cell-based, high-dimensional mass cytometric investigation of the peripheral blood mononuclear cells collected from mice belonging to three groups [normal chow (NC), thioacetamide (TAA), and 11beta-HSD inhibitor drug] was conducted to further understand the pathogenesis of liver fibrosis through reliable noninvasive biomarkers. Firstly, major immune cell types and their population changes were qualitatively analyzed using UMAP dimensionality reduction and two-dimensional visualization technique combined with a conventional manual gating strategy. The population of B cells displayed a twofold increase in the TAA group compared to that in the NC group, which was recovered slightly after treatment with the 11beta-HSD inhibitor drug. In contrast, the populations of NK cells, effector CD4⁺ T cells, and memory CD8⁺ T cells were significantly reduced in the TAA group compared with those in the NC group. Further identification and quantification of the major immune cell types and their subsets were conducted based on automated clustering approaches [PhenoGraph (PG) and FlowSOM]. The B-cell subset corresponding to PhenoGraph cluster PG#2 (CD62L^highCD44^highLy6c^high B cells) and PG#3 (CD62L^highCD44^highLy6c^low B cell) appears to play a major role in both the development of hepatic fibrosis and recovery via treatment, whereas PG#1 (CD62L^lowCD44^highLy6c^low B cell) seems to play a dominant role in the development of hepatic fibrosis. These findings provide insights into the roles of cellular subsets of B cells during the progression of, and recovery from, hepatic fibrosis.

Multiphoton microscopy providing pathological-level quantification of myocardial fibrosis in transplanted human heart

Multiphoton microscopy (MPM), a high-resolution laser scanning technique, has been shown to provide detailed real-time information on fibrosis assessment in animal models. But the value of MPM in human histology, especially in heart tissue, has not been fully explored. We aimed to evaluate the association between myocardial fibrosis measured by MPM and that measured by histological staining in the transplanted human heart. One hundred and twenty samples of heart tissue were obtained from 20 patients consisting of 10 dilated cardiomyopathies (DCM) and 10 ischemic cardiomyopathies (ICM). MPM and picrosirius red staining were performed to quantify collagen volume fraction (CVF) in explanted hearts postoperatively. Cardiomyocyte and myocardial fibrosis could be clearly visualized by MPM. Although patients with ICM had significantly greater MPM-derived CVF than patients with DCM (25.33  ± 12.65 % vs. 19.82  ± 8.62 %, p = 0.006), there was a substantial overlap of CVF values between them. MPM-derived CVF was comparable to that derived from picrosirius red staining based on all samples (22.58 ± 11.13% vs. 21.19 ± 11.79%, p = 0.348), as well as in DCM samples and ICM samples. MPM-derived CVF was correlated strongly with the magnitude of staining-derived CVF in both all samples and DCM samples and ICM samples (r = 0.972, r = 0.963, r = 0.973, respectively; all p < 0.001). Intra- and inter-observer reproducibility for MPM-derived CVF and staining-derived CVF were 0.995, 0.989, 0.995, and 0.985, respectively. Our data demonstrated that MPM can provide a pathological-level assessment of myocardial microstructure in transplanted human heart.

Staging Liver Fibrosis: Comparison of Native T1 Mapping, T2 Mapping, and T1ρ: An Experimental Study in Rats With Bile Duct Ligation and Carbon Tetrachloride at 11.7 T MRI

BACKGROUND

T1, T2, and T1ρ might be potential biomarkers for assessing liver fibrosis. However, few studies reported the value of them in different animal models.

PURPOSE

To investigate and compare the performances of T1, T2, and T1ρ for noninvasively staging liver fibrosis in bile duct ligation (BDL) or carbon tetrachloride (CCl₄ ) model.

STUDY TYPE

Prospective animal model.

SUBJECTS

Liver fibrosis was induced by BDL or injection of CCl₄ in 120 rats.

FIELD STRENGTH/SEQUENCE

11.7 T, T1 mapping with 10 repetition times, T2 mapping with 32 echo times, and T1ρ with 10 spin-lock times.

ASSESSMENT

T1, T2, and T1ρ were measured and correlated with liver fibrosis stages, as well as the degree of inflammation, steatosis, iron deposition, and the expression of cytokeratin 19. The discriminative performance of T1, T2, and T1ρ for staging liver fibrosis was compared.

STATISTICAL TESTS

One-way analysis of variance (ANOVA), Spearman's correlation analysis, factorial design ANOVA, and receiver operating characteristic curves (P < 0.05 was considered statistically significant).

RESULTS

T1, T2, and T1ρ (BDL: rho = 0.73, 0.85, 0.68; CCl₄ : rho = 0.80, 0.29, 0.61) were significantly correlated with liver fibrosis stages, while there was no significant difference in T2 among stage F0-F4 in the CCl₄ model (P = 0.204). The area under the curves (AUCs) range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.76-0.95, 0.89-0.98, and 0.80-0.94 in the CCl₄ model. For the CCl₄ model, the AUCs range of T1, T2, and T1ρ for predicting ≥F1, ≥F2, ≥F3, and F4 were 0.83-0.95, 0.61-0.74, and 0.73-0.89, respectively. T2 had significantly higher AUC in the BDL model than CCl₄ model for diagnosing liver fibrosis.

DATA CONCLUSION

The most sensitive and accurate method for staging liver fibrosis appeared to be T1 in our animal models followed by T1ρ. T2 may not be suitable for evaluating liver fibrosis.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 2.

Improved second harmonic generation and two-photon excitation fluorescence microscopy-based quantitative assessments of liver fibrosis through auto-correction and optimal sampling

BACKGROUND

Second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy is commonly used for the quantitative assessment of liver fibrosis; however, the accuracy is susceptible to sampling error and count error due to disturbances induced by some forms of collagen in liver specimens. In this study, we sought to improve the accuracy of quantitative assessments by removing the effects of this disturbing collagen and optimizing the sampling protocol.

METHODS

Large liver resection samples from 111 patients with chronic hepatitis B were scanned using SHG/TPEF microscopy with multiple adjacent images. During the quantitative assessment, we then removed SHG signals associated with three types of extraneous physiological collagen: large patches of collagen near the boundary of the capsule, collagen around tubular structures, and collagen associated with distorted vessel walls. The optimal sampling protocol was identified by comparing scans from regions of interest of various sizes (3×3 tiles and 5×5 tiles) with full scans of the same tissue.

RESULTS

The proposed auto-correction algorithm detected 88 of 97 (90.7%) disturbing collagen on the images from the validation set. Removing these signals of disturbing collagen improved the correlation between Metavir stage and quantification of all 41 proposed collagen features. Through optimal sampling, five scans of 5×5 tiles or ten scans of 3×3 tiles were sufficient to minimize the mean error rate to around 2% of collagen percentage quantification and to achieve similar correlations around 0.27 with Metavir stage as using full tissue scans.

CONCLUSIONS

Our results demonstrate that the quantitative assessments of liver fibrosis can be greatly enhanced in terms of accuracy and efficiency through optimal sampling and the automated removal of disturbing collagen signals. These types of image processing could be integrated in next-generation SHG/TPEF microscopic systems.

Digital Image Analysis of Picrosirius Red Staining: A Robust Method for Multi-Organ Fibrosis Quantification and Characterization

Current understanding of fibrosis remains incomplete despite the increasing burden of related diseases. Preclinical models are used to dissect the pathogenesis and dynamics of fibrosis, and to evaluate anti-fibrotic therapies. These studies require objective and accurate measurements of fibrosis. Existing histological quantification methods are operator-dependent, organ-specific, and/or need advanced equipment. Therefore, we developed a robust, minimally operator-dependent, and tissue-transposable digital method for fibrosis quantification. The proposed method involves a novel algorithm for more specific and more sensitive detection of collagen fibers stained by picrosirius red (PSR), a computer-assisted segmentation of histological structures, and a new automated morphological classification of fibers according to their compactness. The new algorithm proved more accurate than classical filtering using principal color component (red-green-blue; RGB) for PSR detection. We applied this new method on established mouse models of liver, lung, and kidney fibrosis and demonstrated its validity by evidencing topological collagen accumulation in relevant histological compartments. Our data also showed an overall accumulation of compact fibers concomitant with worsening fibrosis and evidenced topological changes in fiber compactness proper to each model. In conclusion, we describe here a robust digital method for fibrosis analysis allowing accurate quantification, pattern recognition, and multi-organ comparisons useful to understand fibrosis dynamics.

Characterization of pathological thyroid tissue using polarization-sensitive second harmonic generation microscopy

Polarization-sensitive second harmonic generation (SHG) microscopy is an established imaging technique able to provide information related to specific molecular structures including collagen. In this investigation, polarization-sensitive SHG microscopy was used to investigate changes in the collagen ultrastructure between histopathology slides of normal and diseased human thyroid tissues including follicular nodular disease, Grave's disease, follicular variant of papillary thyroid carcinoma, classical papillary thyroid carcinoma, insular or poorly differentiated carcinoma, and anaplastic or undifferentiated carcinoma ex vivo. The second-order nonlinear optical susceptibility tensor component ratios, χ⁽²⁾_zzz'/χ⁽²⁾_zxx' and χ⁽²⁾_xyz'/χ⁽²⁾_zxx', were obtained, where χ⁽²⁾_zzz'/χ⁽²⁾_zxx' is a structural parameter and χ⁽²⁾_xyz'/χ⁽²⁾_zxx' is a measure of the chirality of the collagen fibers. Furthermore, the degree of linear polarization (DOLP) of the SHG signal was measured. A statistically significant increase in χ⁽²⁾_zzz'/χ⁽²⁾_zxx' values for all the diseased tissues except insular carcinoma and a statistically significant decrease in DOLP for all the diseased tissues were observed compared to normal thyroid. This finding indicates a higher ultrastructural disorder in diseased collagen and provides an innovative approach to discriminate between normal and diseased thyroid tissues that is complementary to standard histopathology.

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.

Liver-Targeted siRNA Lipid Nanoparticles Treat Hepatic Cirrhosis by Dual Antifibrotic and Anti-inflammatory Activities

Previous studies on the treatment of hepatic cirrhosis have been focusing on how to inhibit liver fibrosis, while ignoring liver inflammation, a key and underlying factor that promotes cirrhosis. High mobility group box-1 (HMGB1) protein, a pro-inflammatory factor and fibroblast chemokine, can promote the proliferation of hepatic stellate cells (HSCs) and the development of hepatic inflammation and fibrosis, playing a key role in cirrhosis formation. In this study, we prepared pPB peptide (C*SRNLIDC*)-modified and HMGB1-siRNA-loaded stable nucleic acid lipid nanoparticles (HMGB1-siRNA@SNALP-pPB) to effectively treat hepatic cirrhosis by their dual antifibrotic and anti-inflammatory activities. The pPB peptide-modified and heat shock protein 47 (HSP47)-siRNA-loaded stable nucleic acid lipid nanoparticles (HSP47-siRNA@SNALP-pPB), which have only an antifibrotic effect without an anti-inflammatory effect, was used as control. The results demonstrated that HMGB1-siRNA@SNALP-pPB were actively targeted to HSCs by the mediation of pPB peptide, effectively silenced the HMGB1 gene, inhibited the activation and proliferation of HSCs, reduced the release of HMGB1 protein, inhibited collagen deposition and fibrosis formation in the liver, and significantly prolonged the survival time of cirrhotic mice models. HMGB1-siRNA@SNALP-pPB showed a stronger therapeutic effect on liver cirrhosis than HSP47-siRNA@SNALP-pPB. This study provides an actively targeted siRNA delivery system for cirrhosis treatment based on the dual antifibrotic and anti-inflammatory effects. In addition, this study clarified the role of inflammatory problems in cirrhosis treatment in addition to liver fibrosis, providing a useful idea and scientific basis for the development of cirrhosis treatment strategies in the future.

Improved quantitative assessment of HBV-associated liver fibrosis using second-harmonic generation microscopy with feature selection

BACKGROUND AND AIM

Quantitative assessments of liver fibrosis using second-harmonic generation/two-photon excited fluorescence microscopy provide greater sensitivity and accuracy than collagen proportionate area while eliminating operator-dependent variation in the staining process. In conjunction with sophisticated image analysis algorithms and feature selection, we might reduce the computation cost in future and narrow down the candidates for further clinical studies.

METHODS

We sampled a total of 244 liver specimens from patients with hepatitis B viral infections who underwent liver biopsy or liver resection at the National Taiwan University Hospital. The samples were then imaged using a Genesis (HistoIndex Pte. Ltd, Singapore) system, wherein second-harmonic generation microscopy was used to visualize collagen, and two-photon excited fluorescence microscopy was used to visualize other cell structures. We used 100 morphological features extracted from the images to assess correlations with METAVIR fibrosis scores.

RESULTS

Out of 100 quantitative measurements, 76 showed significant correlation with METAVIR scoring, thereby enabling the statistical discrimination of patients in various stages of the disease. These 76 features were also narrowed down by the nonlinear test to 10 candidate measurements, which can be further investigated in detail.

CONCLUSIONS

Our experimental results showed that the model with 10 selected features can beat the one with second-harmonic generation only, and performed equivalently well compared the model with 76 features, especially for early-stage discrimination. Features presenting significant correlation were used to fit a single combined index in order to predict pathological staging, thereby making it possible to reveal incremental progress during treatment.

Locostatin Alleviates Liver Fibrosis Induced by Carbon Tetrachloride in Mice

BACKGROUND AND AIMS

Liver fibrosis is featured with excessive deposition of extracellular matrix and fibrous connective tissue hyperplasia. The specific inhibitor of Raf-1 kinase inhibitor protein, locostatin, inhibits the migration of hepatic stellate cells. In this study, we investigated the effect of locostatin on liver fibrosis and its underlying mechanism.

METHODS

Carbon tetrachloride (CCl4) was used to induce liver fibrosis in mice, and locostatin was injected intraperitoneally. Liver fibrosis was assessed by Masson and Sirius red staining, hydroxyproline (HYP) assay, and collagen percentage area. Collagen I, collagen III, and α-SMA were detected by RT-PCR and western blot. The levels of MMP-13, MMP-2, TIMP-1, and TIMP-2 were estimated by ELISA. Liver inflammation was evaluated by HE staining and immunohistochemistry; liver myeloperoxidase (MPO), superoxide dismutase, and malondialdehyde were measured by ELISA; and cytokines were by Mouse Cytokine Array Q4000.

RESULTS

Compared to the CCl4 group, HYP (208.56 ± 6.12) µg/g, percentage of total collagen at overall region (1.91 ± 0.13), MMP-13/TIMP-1 (0.19 ± 0.01), MPO (1.45 ± 0.04) U/g, TGF-β (2652 ± 91.20), PDGF-AA (3897 ± 290.69), and E-selectin (1569 ± 66.48) in the liver tissues were decreased significantly in the locostatin-treated group.

CONCLUSIONS

Locostatin mitigated liver fibrosis and inflammation induced by CCl4. The mechanism is via inhibition inflammatory cytokines, TGF-β, PDGF-AA, and E-selectin.

The Role of Phospho-c-Jun N-Terminal Kinase Expression on hepatocyte Necrosis and Autophagy in the Cholestatic Liver

BACKGROUND

Clinically, liver fibrosis and cholestasis are two major disease entities, ultimately leading to hepatic failure. Although autophagy plays a substantial role in the pathogenesis of these diseases, its precise mechanism has not been determined yet.

MATERIALS AND METHODS

Mouse models of liver fibrosis or cholestasis were obtained after the serial administration of thioacetamide (TAA) or surgical bile duct ligation (BDL), respectively. Then, after obtaining liver specimens at specific time points, we compared the expression of makers related to apoptosis (cleaved caspases), inflammation (CD68), necrosis (high-mobility group box 1), phospho-c-Jun N-terminal kinase (p-JNK), and autophagy (microtubule-associated protein light chain 3B and p62) in the fibrotic or cholestatic mouse livers, by polymerase chain reaction, Western blot analysis, immunohistochemistry, and immunofluorescence.

RESULTS

Although cholestatic livers exhibited the tendency of progressively increasing the expression of most apoptosis-related markers (cleaved caspases), it was not prominent when it was compared with the tendency found in the livers of TAA-treated mice. Contrastingly, the necrosis-related factor (high-mobility group box 1) was significantly increased in the livers of BDL mice over time, reaching their peak values on day 7 after BDL. In addition, the inflammation-related factor (CD68) was highly expressed in BDL mice compared with TAA-treated mice over time. Autophagy marker studies indicated that autophagy was upregulated in fibrotic livers, whereas it was downregulated in cholestatic livers. We also observed mild to moderate activation of p-JNK in the livers of TAA-treated mice, whereas significantly higher p-JNK activation was detected in the livers of BDL mice.

CONCLUSIONS

Unlike TAA-treated mice, BDL mice exhibited higher expression of the markers related with inflammation and necrosis, especially including p-JNK, while maintaining low levels of autophagic process. Therefore, obstructive cholestasis is characterized by higher p-JNK activation, which could be related with marked necrotic cell death resulting from extensive inflammation and little chance of compensatory autophagy.

Current Models of Fatty Liver Disease; New Insights, Therapeutic Targets and Interventions

Non-alcoholic fatty liver disease (NAFLD) encompasses a spectrum of disorders ranging from simple steatosis to steatosis with inflammation and fibrosis. NAFLD is currently the most prevalent chronic liver disease worldwide, with a global prevalence of 25%, and is soon projected to be the leading cause for liver transplantation in the US. Alarmingly, few effective pharmacotherapeutic approaches are currently available to block or attenuate development and progression of NAFLD. Preclinical models are critical for unraveling the complex and multi-factorial etiology of NAFLD and for testing potential therapeutics. Here we review preclinical models that have been instrumental in highlighting molecular and cellular mechanisms underlying the pathogenesis of NAFLD and in facilitating early proof-of-concept investigations into novel intervention strategies.

Chemical induction of hepatic apoptosis in rodents

The urge of identifying new pharmacological interventions to prevent or attenuate liver injury is of critical importance and needs an expanded experimental toolbox. Hepatocyte injury and cellular death is a prominent feature behind the pathology of liver diseases. Several research activities focused on identifying chemicals and hepatotoxicants that induce cell death by apoptosis, in addition to presenting its corresponding signaling pathway. Although such efforts provided further understanding of the mechanisms of cell death, it has also raised confusion concerning identifying the involvement of several modes of cell death including apoptosis, necrosis and fibrosis. The current review highlights the ability of several chemicals and potential hepatotoxicants to induce liver damage in rodents by means of apoptosis while the probable involvement of other modes of cell death is also exposed. Thus, several chemical substances including hepatotoxins, mycotoxins, hyperglycemia inducers, metallic nanoparticles and immunosuppressant drugs are reviewed to explore the hepatic cytotoxic spectrum they could exert on hepatocytes of rodents. In addition, the current review address the mechanism by which hepatotoxicity is initiated in hepatocytes in different rodents aiding the researcher in choosing the right animal model for a better research outcome.

Serum and Hepatic Autofluorescence as a Real-Time Diagnostic Tool for Early Cholestasis Assessment

While it is well established that various factors can impair the production and flow of bile and lead to cholestatic disease in hepatic and extrahepatic sites, an enhanced assessment of the biomarkers of the underlying pathophysiological mechanisms is still needed to improve early diagnosis and therapeutic strategies. Hence, we investigated fluorescing endogenous biomolecules as possible intrinsic biomarkers of molecular and cellular changes in cholestasis. Spectroscopic autofluorescence (AF) analysis was performed using a fiber optic probe (366 nm excitation), under living conditions and in serum, on the livers of male Wistar rats submitted to bile duct ligation (BDL, 24, 48, and 72 h). Biomarkers of liver injury were assayed biochemically. In the serum, AF analysis distinctly detected increased bilirubin at 24 h BDL. A continuous, significant increase in red-fluorescing porphyrin derivatives indicated the subversion of heme metabolism, consistent with an almost twofold increase in the serum iron at 72 h BDL. In the liver, changes in the AF of NAD(P)H and flavins, as well as lipopigments, indicated the impairment of mitochondrial functionality, oxidative stress, and the accumulation of oxidative products. A serum/hepatic AF profile can be thus proposed as a supportive diagnostic tool for the in situ, real-time study of bio-metabolic alterations in bile duct ligation (BDL) in experimental hepatology, with the potential to eventually translate to clinical diagnosis.

Autofluorescence-based optical biopsy: An effective diagnostic tool in hepatology

Autofluorescence emission of liver tissue depends on the presence of endogenous biomolecules able to fluoresce under suitable light excitation. Overall autofluorescence emission contains much information of diagnostic value because it is the sum of individual autofluorescence contributions from fluorophores involved in metabolism, for example, NAD(P)H, flavins, lipofuscins, retinoids, porphyrins, bilirubin and lipids, or in structural architecture, for example, fibrous proteins, in close relationship with normal, altered or diseased conditions of the liver. Since the 1950s, hepatocytes and liver have been historical models to study NAD(P)H and flavins as in situ, real-time autofluorescence biomarkers of energy metabolism and redox state. Later investigations designed to monitor organ responses to ischaemia/reperfusion were able to predict the risk of dysfunction in surgery and transplantation or support the development of procedures to ameliorate the liver outcome. Subsequently, fluorescent fatty acids, lipofuscin-like lipopigments and collagen were characterized as optical biomarkers of liver steatosis, oxidative stress damage, fibrosis and disease progression. Currently, serum AF is being investigated to improve non-invasive optical diagnosis of liver disease. Validation of endogenous fluorophores and in situ discrimination of cancerous from non-cancerous tissue belong to the few studies on liver in human subjects. These reports along with other optical techniques and the huge work performed on animal models suggest many optically based applications in hepatology. Optical diagnosis is currently offering beneficial outcomes in clinical fields ranging from the respiratory and gastrointestinal tracts, to dermatology and ophthalmology. Accordingly, this review aims to promote an effective bench to bedside transfer in hepatology.

INT-767 improves histopathological features in a diet-induced ob/ob mouse model of biopsy-confirmed non-alcoholic steatohepatitis

AIM

To characterize the efficacy of the dual FXR/TGR5 receptor agonist INT-767 upon histological endpoints in a rodent model of diet-induced and biopsy-confirmed non-alcoholic steatohepatitis (NASH).

METHODS

The effects of INT-767 on histological features of NASH were assessed in two studies using Lep^ob/ob (ob/ob) NASH mice fed the AMLN diet (high fat with trans-fat, cholesterol and fructose). In a proof-of-concept study, Lep^ob/ob (ob/ob) NASH mice were first dosed with INT-767 (3 or 10 mg/kg for 8 wk). A second ob/ob NASH study compared INT-767 (3 and 10 mg/kg) to obeticholic acid (OCA) (10 or 30 mg/kg; 16 wk). Primary histological endpoints included qualitative and quantitative assessments of NASH. Other metabolic and plasma endpoints were also assessed. A comparative assessment of INT-767 and OCA effects on drug distribution and hepatic gene expression was performed in C57Bl/6 mice on standard chow. C57Bl/6 mice were orally dosed with INT-767 or OCA (1-30 mg/kg) for 2 wk, and expression levels of candidate genes were assessed by RNA sequencing and tissue drug levels were measured by liquid chromatography tandem-mass spectrometry.

RESULTS

INT-767 dose-dependently (3 and 10 mg/kg, PO, QD, 8 wk) improved qualitative morphometric scores on steatohepatitis severity, inflammatory infiltrates and fibrosis stage. Quantitative morphometric analyses revealed that INT-767 reduced parenchymal collagen area, collagen fiber density, inflammation (assessed by Galectin-3 immunohistochemistry) and hepatocyte lipid droplet area following INT-767 treatment. In a comparative study (16 wk), the FXR agonists OCA (10 and 30 mg/kg) and INT-767 (3 and 10 mg/kg) both improved NASH histopathology, with INT-767 exerting greater therapeutic potency and efficacy than OCA. Mechanistic studies suggest that both drugs accumulate similarly within the liver and ileum, however, the effects of INT-767 may be driven by enhanced hepatic, but not ileal, FXR function.

CONCLUSION

These findings confirm the potential utility of FXR and dual FXR/TGR5 activation as disease intervention strategies in NASH.

Assessment of Fatty Liver in Models of Disease Programming

Nonalcoholic fatty liver disease (NAFLD) is currently the most common cause of chronic liver disease worldwide and is present in a third of the general population and the majority of individuals with obesity and type 2 diabetes. Importantly, NAFLD can progress to severe nonalcoholic steatohepatitis (NASH), associated with liver failure and hepatocellular carcinoma. Recent research efforts have extensively focused on identifying factors contributing to the additional "hit" required to promote NALFD disease progression. The maternal diet, and in particular a high-fat diet (HFD), may be one such hit "priming" the development of severe fatty liver disease, a notion supported by the increasing incidence of NAFLD among children and adolescents in Westernized countries. In recent years, a plethora of key studies have used murine models of maternal obesity to identify fundamental mechanisms such as lipogenesis, mitochondrial function, inflammation, and fibrosis that may underlie the developmental priming of NAFLD. In this chapter, we will address key considerations for constructing experimental models and both conventional and advanced methods of quantifying NAFLD disease status.