Nonlinear optical microscopy: use of second harmonic generation and two-photon microscopy for automated quantitative liver fibrosis studies

A male mouse model for metabolic dysfunction-associated steatotic liver disease and hepatocellular carcinoma

The lack of an appropriate preclinical model of metabolic dysfunction-associated steatotic liver disease (MASLD) that recapitulates the whole disease spectrum impedes exploration of disease pathophysiology and the development of effective treatment strategies. Here, we develop a mouse model (Streptozotocin with high-fat diet, STZ + HFD) that gradually develops fatty liver, metabolic dysfunction-associated steatohepatitis (MASH), hepatic fibrosis, and hepatocellular carcinoma (HCC) in the context of metabolic dysfunction. The hepatic transcriptomic features of STZ + HFD mice closely reflect those of patients with obesity accompanying type 2 diabetes mellitus, MASH, and MASLD-related HCC. Dietary changes and tirzepatide administration alleviate MASH, hepatic fibrosis, and hepatic tumorigenesis in STZ + HFD mice. In conclusion, a murine model recapitulating the main histopathologic, transcriptomic, and metabolic alterations observed in MASLD patients is successfully established.

Liver biopsy evaluation in MASH drug development: Think thrice, act wise

During recent decades, the metabolic dysfunction-associated steatohepatitis (MASH) field has witnessed several paradigm shifts, including the recognition of liver fibrosis as the main predictor of major adverse liver outcomes. Throughout this evolution, liver histology has been recognised as one of the main hurdles in MASH drug development due to its invasive nature, associated cost, and high inter- and intra-reader variability. Collective experience demonstrates the importance of consistency in the central reading process, where consensus methods have emerged as appropriate ways to mitigate against well-known challenges. Using crystalized knowledge in the field, stakeholders should collectively work towards the next paradigm shift, where non-invasive biomarkers will be considered surrogate endpoints for accelerated approval. In this review, we provide an overview of the evolution of the regulatory histology endpoints and the liver biopsy reading process, within the MASH trial landscape, over recent decades; we then review the biggest challenges associated with liver biopsy endpoints. Finally, we discuss and provide recommendations on the best practices for liver biopsy evaluation in MASH drug development.

Nonlinear Optical Properties of 2D Materials and their Applications

2D materials are a subject of intense research in recent years owing to their exclusive photoelectric properties. With giant nonlinear susceptibility and perfect phase matching, 2D materials have marvelous nonlinear light-matter interactions. The nonlinear optical properties of 2D materials are of great significance to the design and analysis of applied materials and functional devices. Here, the fundamental of nonlinear optics (NLO) for 2D materials is introduced, and the methods for characterizing and measuring second-order and third-order nonlinear susceptibility of 2D materials are reviewed. Furthermore, the theoretical and experimental values of second-order susceptibility χ(2) and third-order susceptibility χ(3) are tabulated. Several applications and possible future research directions of second-harmonic generation (SHG) and third-harmonic generation (THG) for 2D materials are presented.

Digital pathology and spatial omics in steatohepatitis: Clinical applications and discovery potentials

Steatohepatitis with diverse etiologies is the most common histological manifestation in patients with liver disease. However, there are currently no specific histopathological features pathognomonic for metabolic dysfunction-associated steatotic liver disease, alcohol-associated liver disease, or metabolic dysfunction-associated steatotic liver disease with increased alcohol intake. Digitizing traditional pathology slides has created an emerging field of digital pathology, allowing for easier access, storage, sharing, and analysis of whole-slide images. Artificial intelligence (AI) algorithms have been developed for whole-slide images to enhance the accuracy and speed of the histological interpretation of steatohepatitis and are currently employed in biomarker development. Spatial biology is a novel field that enables investigators to map gene and protein expression within a specific region of interest on liver histological sections, examine disease heterogeneity within tissues, and understand the relationship between molecular changes and distinct tissue morphology. Here, we review the utility of digital pathology (using linear and nonlinear microscopy) augmented with AI analysis to improve the accuracy of histological interpretation. We will also discuss the spatial omics landscape with special emphasis on the strengths and limitations of established spatial transcriptomics and proteomics technologies and their application in steatohepatitis. We then highlight the power of multimodal integration of digital pathology augmented by machine learning (ML)algorithms with spatial biology. The review concludes with a discussion of the current gaps in knowledge, the limitations and premises of these tools and technologies, and the areas of future research.

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.

Digital pathology for nonalcoholic steatohepatitis assessment

Histological assessment of nonalcoholic fatty liver disease (NAFLD) has anchored knowledge development about the phenotypes of the condition, their natural history and their clinical course. This fact has led to the use of histological assessment as a reference standard for the evaluation of efficacy of drug interventions for nonalcoholic steatohepatitis (NASH) - the more histologically active form of NAFLD. However, certain limitations of conventional histological assessment systems pose challenges in drug development. These limitations have spurred intense scientific and commercial development of machine learning and digital approaches towards the assessment of liver histology in patients with NAFLD. This research field remains an area in rapid evolution. In this Perspective article, we summarize the current conventional assessment of NASH and its limitations, the use of specific digital approaches for histological assessment, and their application to the study of NASH and its response to therapy. Although this is not a comprehensive review, the leading tools currently used to assess therapeutic efficacy in drug development are specifically discussed. The potential translation of these approaches to support routine clinical assessment of NAFLD and an agenda for future research are also discussed.

AutoFibroNet: A deep learning and multi-photon microscopy-derived automated network for liver fibrosis quantification in MAFLD

BACKGROUND

Liver fibrosis is the strongest histological risk factor for liver-related complications and mortality in metabolic dysfunction-associated fatty liver disease (MAFLD). Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) is a powerful tool for label-free two-dimensional and three-dimensional tissue visualisation that shows promise in liver fibrosis assessment.

AIM

To investigate combining multi-photon microscopy (MPM) and deep learning techniques to develop and validate a new automated quantitative histological classification tool, named AutoFibroNet (Automated Liver Fibrosis Grading Network), for accurately staging liver fibrosis in MAFLD.

METHODS

AutoFibroNet was developed in a training cohort that consisted of 203 Chinese adults with biopsy-confirmed MAFLD. Three deep learning models (VGG16, ResNet34, and MobileNet V3) were used to train pre-processed images and test data sets. Multi-layer perceptrons were used to fuse data (deep learning features, clinical features, and manual features) to build a joint model. This model was then validated in two further independent cohorts.

RESULTS

AutoFibroNet showed good discrimination in the training set. For F0, F1, F2 and F3-4 fibrosis stages, the area under the receiver operating characteristic curves (AUROC) of AutoFibroNet were 1.00, 0.99, 0.98 and 0.98. The AUROCs of F0, F1, F2 and F3-4 fibrosis stages for AutoFibroNet in the two validation cohorts were 0.99, 0.83, 0.80 and 0.90 and 1.00, 0.83, 0.80 and 0.94, respectively, showing a good discriminatory ability in different cohorts.

CONCLUSION

AutoFibroNet is an automated quantitative tool that accurately identifies histological stages of liver fibrosis in Chinese individuals with MAFLD.

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.

Caloric Restriction Combined with Immobilization as Translational Model for Sarcopenia Expressing Key-Pathways of Human Pathology

The prevalence of sarcopenia is increasing while it is often challenging, expensive and time-consuming to test the effectiveness of interventions against sarcopenia. Translational mouse models that adequately mimic underlying physiological pathways could accelerate research but are scarce. Here, we investigated the translational value of three potential mouse models for sarcopenia, namely partial immobilized (to mimic sedentary lifestyle), caloric restricted (CR; to mimic malnutrition) and a combination (immobilized & CR) model. C57BL/6J mice were calorically restricted (-40%) and/or one hindleg was immobilized for two weeks to induce loss of muscle mass and function. Muscle parameters were compared to those of young control (4 months) and old reference mice (21 months). Transcriptome analysis of quadriceps muscle was performed to identify underlying pathways and were compared with those being expressed in aged human vastus lateralis muscle-biopsies using a meta-analysis of five different human studies. Caloric restriction induced overall loss of lean body mass (-15%, p<0.001), whereas immobilization decreased muscle strength (-28%, p<0.001) and muscle mass of hindleg muscles specifically (on average -25%, p<0.001). The proportion of slow myofibers increased with aging in mice (+5%, p<0.05), and this was not recapitulated by the CR and/or immobilization models. The diameter of fast myofibers decreased with aging (-7%, p<0.05), and this was mimicked by all models. Transcriptome analysis revealed that the combination of CR and immobilization recapitulated more pathways characteristic for human muscle-aging (73%) than naturally aged (21 months old) mice (45%). In conclusion, the combination model exhibits loss of both muscle mass (due to CR) and function (due to immobilization) and has a remarkable similarity with pathways underlying human sarcopenia. These findings underline that external factors such as sedentary behavior and malnutrition are key elements of a translational mouse model and favor the combination model as a rapid model for testing the treatments against sarcopenia.

Pilose antler extract restores type I and III collagen to accelerate wound healing

Granulation tissue has supporting and filling functions in wound healing. The collagen produced by fibroblast acts as a cell scaffold in the granulation tissue to facilitate the formation of new blood vessels and epithelial coverage. Previously, we extracted protein components from the pilose antler that was involved in the biological process of collagen fibril organization. They were also found to contain abundant extracellular matrix(ECM) components. Therefore, in this experiment, we used a rat model of full-thickness skin excision and fibroblasts to perform an experiment for determination of the effects of pilose antler protein extract (PAE) on collagen content and fiber synthesis during wound healing. Additionally, we further analyzed its pharmacological effects on wound healing and the possible regulatory mechanisms. We found that PAE accelerated synthesis of type I and III collagen, promoted the formation of type III collagen fibers, and reduced collagen degradation by recruiting fibroblasts. Furthermore, the extract upregulated the expression of TGF β R1 and Smad2, and initiated the entry of Smad2/Smad3 into the nucleus. After adding SB431542 to inhibit TGF-β type I receptor activity, PAE's ability to promote Smad2/Smad3 nuclear localization was weakened. These data indicate that local PAE therapy can promote the proliferation of fibroblasts, dynamically regulate the expression of TGF-β, and increase the amount of collagen and the synthesis of type III collagen fibers by promoting smad2 activity in the proliferation period, thus accelerating the regenerative healing of wounds.

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.

Artificial intelligence and deep learning: new tools for histopathological diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis

Nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH) is associated with metabolic syndrome and is rapidly increasing globally with the increased prevalence of obesity. Although noninvasive diagnosis of NAFLD/NASH has progressed, pathological evaluation of liver biopsy specimens remains the gold standard for diagnosing NAFLD/NASH. However, the pathological diagnosis of NAFLD/NASH relies on the subjective judgment of the pathologist, resulting in non-negligible interobserver variations. Artificial intelligence (AI) is an emerging tool in pathology to assist diagnoses with high objectivity and accuracy. An increasing number of studies have reported the usefulness of AI in the pathological diagnosis of NAFLD/NASH, and our group has already used it in animal experiments. In this minireview, we first outline the histopathological characteristics of NAFLD/NASH and the basics of AI. Subsequently, we introduce previous research on AI-based pathological diagnosis of NAFLD/NASH.

The role of altered lipid composition and distribution in liver fibrosis revealed by multimodal nonlinear optical microscopy

Intracellular lipid accumulation is commonly seen in fibrotic livers, but its exact role in liver fibrosis remains elusive. Here, we established a multimodal nonlinear optical microscopy to quantitatively map distribution of biomolecules in fibrotic livers. Our data revealed that unsaturated triglycerides were predominantly accumulated in central vein area during liver fibrosis but not in portal vein area. Moreover, the lipid homeostasis was remarkably dysregulated in the late-stage compared to the early-stage fibrosis, including increased unsaturated triglycerides with decreased lipid unsaturation degree and decreased membrane fluidity. Such alterations were likely due to up-regulated lipogenesis, desaturation, and peroxidation, which consequently led to endoplasmic reticulum stress and cell death. Inspiringly, injured hepatocyte could be rescued by remodeling lipid homeostasis via either supply of unsaturated fatty acids or enhancement of membrane fluidity. Collectively, our study improves current understanding of the role of lipid homeostasis in fibrosis and open opportunities for treatment.

Digital pathology with artificial intelligence analyses provides greater insights into treatment-induced fibrosis regression in NASH

BACKGROUND & AIMS

Liver fibrosis is a key prognostic determinant for clinical outcomes in non-alcoholic steatohepatitis (NASH). Current scoring systems have limitations, especially in assessing fibrosis regression. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence analyses provides standardized evaluation of NASH features, especially liver fibrosis and collagen fiber quantitation on a continuous scale. This approach was applied to gain in-depth understanding of fibrosis dynamics after treatment with tropifexor (TXR), a non-bile acid farnesoid X receptor agonist in patients participating in the FLIGHT-FXR study (NCT02855164).

METHOD

Unstained sections from 198 liver biopsies (paired: baseline and end-of-treatment) from 99 patients with NASH (fibrosis stage F2 or F3) who received placebo (n = 34), TXR 140 μg (n = 37), or TXR 200 μg (n = 28) for 48 weeks were examined. Liver fibrosis (qFibrosis®), hepatic fat (qSteatosis®), and ballooned hepatocytes (qBallooning®) were quantitated using SHG/TPEF microscopy. Changes in septa morphology, collagen fiber parameters, and zonal distribution within liver lobules were also quantitatively assessed.

RESULTS

Digital analyses revealed treatment-associated reductions in overall liver fibrosis (qFibrosis®), unlike conventional microscopy, as well as marked regression in perisinusoidal fibrosis in patients who had either F2 or F3 fibrosis at baseline. Concomitant zonal quantitation of fibrosis and steatosis revealed that patients with greater qSteatosis reduction also have the greatest reduction in perisinusoidal fibrosis. Regressive changes in septa morphology and reduction in septa parameters were observed almost exclusively in F3 patients, who were adjudged as 'unchanged' with conventional scoring.

CONCLUSION

Fibrosis regression following hepatic fat reduction occurs initially in the perisinusoidal regions, around areas of steatosis reduction. Digital pathology provides new insights into treatment-induced fibrosis regression in NASH, which are not captured by current staging systems.

LAY SUMMARY

The degree of liver fibrosis (tissue scarring) in non-alcoholic steatohepatitis (NASH) is the main predictor of negative clinical outcomes. Accurate assessment of the quantity and architecture of liver fibrosis is fundamental for patient enrolment in NASH clinical trials and for determining treatment efficacy. Using digital microscopy with artificial intelligence analyses, the present study demonstrates that this novel approach has greater sensitivity in demonstrating treatment-induced reversal of fibrosis in the liver than current systems. Furthermore, additional details are obtained regarding the pathogenesis of NASH disease and the effects of therapy.

Non-Invasive Skin Imaging Assessment of Human Stress During Head-Down Bed Rest Using a Portable Handheld Two-Photon Microscope

Spaceflight presents a series of physiological and pathological challenges to astronauts resulting from ionizing radiation, microgravity, isolation, and other spaceflight hazards. These risks cause a series of aging-related diseases associated with increased oxidative stress and mitochondria dysfunction. The skin contains many autofluorescent substances, such as nicotinamide adenine dinucleotide phosphate (NAD(P)H), keratin, melanin, elastin, and collagen, which reflect physiological and pathological changes in vivo. In this study, we used a portable handheld two-photon microscope to conduct high-resolution in vivo skin imaging on volunteers during 15 days of head-down bed rest. The two-photon microscope, equipped with a flexible handheld scanning head, was used to measure two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) images of the left forearm, left front chest, and forehead of volunteers. Changes in TPEF, SHG, and the extended SHG-to-AF(TPEF) aging index of the dermis (SAAID) were measured. It was found that TPEF intensity increased during bed rest and was restored to normal levels after recovery. Meanwhile, SHG increased slightly during bed rest, and the skin aging index increased. Moreover, we found the skin TPEF signals of the left forearm were significantly negatively associated with the oxidative stress marker malondialdehyde (MDA) and DNA damage marker 8-hydroxy-2′-desoxyguanosine (8-OHdG) values of subjects during head-down bed rest. Meanwhile, the SHG signals were also significantly negatively correlated with MDA and 8-OHDG. A significant negative correlation between the extended SAAID of the left chest and serum antioxidant superoxide dismutase (SOD) levels was also found. These results demonstrate that skin autofluorescence signals can reflect changes in human oxidant status. This study provides evidence for in-orbit monitoring of changes in human stress using a portable handheld two-photon microscope for skin imaging.

Identification of human ovarian cancer relying on collagen fiber coverage features by quantitative second harmonic generation imaging

Ovarian cancer has the highest mortality rate among all gynecological cancers, containing complicated heterogeneous histotypes, each with different treatment plans and prognoses. The lack of screening test makes new perspectives for the biomarker of ovarian cancer of great significance. As the main component of extracellular matrix, collagen fibers undergo dynamic remodeling caused by neoplastic activity. Second harmonic generation (SHG) enables label-free, non-destructive imaging of collagen fibers with submicron resolution and deep sectioning. In this study, we developed a new metric named local coverage to quantify morphologically localized distribution of collagen fibers and combined it with overall density to characterize 3D SHG images of collagen fibers from normal, benign and malignant human ovarian biopsies. An overall diagnosis accuracy of 96.3% in distinguishing these tissue types made local and overall density signatures a sensitive biomarker of tumor progression. Quantitative, multi-parametric SHG imaging might serve as a potential screening test tool for ovarian cancer.

Loxin Reduced the Inflammatory Response in the Liver and the Aortic Fatty Streak Formation in Mice Fed with a High-Fat Diet

Oxidized low-density lipoprotein (ox-LDL) is the most harmful form of cholesterol associated with vascular atherosclerosis and hepatic injury, mainly due to inflammatory cell infiltration and subsequent severe tissue injury. Lox-1 is the central ox-LDL receptor expressed in endothelial and immune cells, its activation regulating inflammatory cytokines and chemotactic factor secretion. Recently, a Lox-1 truncated protein isoform lacking the ox-LDL binding domain named LOXIN has been described. We have previously shown that LOXIN overexpression blocked Lox-1-mediated ox-LDL internalization in human endothelial progenitor cells in vitro. However, the functional role of LOXIN in targeting inflammation or tissue injury in vivo remains unknown. In this study, we investigate whether LOXIN modulated the expression of Lox-1 and reduced the inflammatory response in a high-fat-diet mice model. Results indicate that human LOXIN blocks Lox-1 mediated uptake of ox-LDL in H4-II-E-C3 cells. Furthermore, in vivo experiments showed that overexpression of LOXIN reduced both fatty streak lesions in the aorta and inflammation and fibrosis in the liver. These findings were associated with the down-regulation of Lox-1 in endothelial cells. Then, LOXIN prevents hepatic and aortic tissue damage in vivo associated with reduced Lox-1 expression in endothelial cells. We encourage future research to understand better the underlying molecular mechanisms and potential therapeutic use of LOXIN.

Multi-photon microscopy for the evaluation of interstitial fibrosis in extended criteria donor kidneys: A Proof-of-Concept Study

INTRODUCTION

To evaluate the initial use of label-free second harmonic generation (SHG) imaging with two-photon excitation (2PE) auto-fluorescence in multi-photon microscopy (MPM) for the quantification of collagen/fibrosis on pre-implantation biopsies of extended criteria donors (ECD).

MATERIALS AND METHODS

20 pre-implantation core biopsies were extracted from 10 donor kidney samples, of which originated from 7 donors. Kidney Donor Profile Index (KDPI) and Remuzzi scores of biopsies were calculated. Collagen parameters measured included quantification by the Collagen Area Ratio in Total Tissue (CART) and qualitative measurements by Collagen Reticulation Index (CRI).

RESULTS

Biopsies classified with > 85% KDPI scores had significantly higher CART (p = 0.011) and lower CRI values (p = 0.025) than biopsies with ≤ 85% KDPI scores. Increase in CRI values correlated significantly with rise in recipient creatinine levels 1-year post-transplant (p = 0.027; 95% CI: 4.635-66.797).

CONCLUSION

MPM is an evolving technology that enables the quantification of the amount (CART) and quality (CRI) of collagen deposition in unstained pre-implantation biopsies of donor kidneys stratified by KDPI scores. This initial evaluation found significant differences in both parameters between donor kidneys with more or less than 85% KDPI. This article is protected by copyright. All rights reserved.

Assessment of Ultra-Early-Stage Liver Fibrosis in Human Non-Alcoholic Fatty Liver Disease by Second-Harmonic Generation Microscopy

Non-alcoholic fatty liver disease (NAFLD) is associated with the chronic progression of fibrosis. In general, the progression of liver fibrosis is determined by a histopathological assessment with a collagen-stained section; however, the ultra-early stage of liver fibrosis is challenging to identify because of the low sensitivity in the collagen-selective staining method. In the present study, we demonstrate the feasibility of second-harmonic generation (SHG) microscopy in the histopathological diagnosis of the liver of NAFLD patients for the quantitative assessment of the ultra-early stage of fibrosis. We investigated four representative NAFLD patients with early stages of fibrosis. SHG microscopy visualised well-matured fibrotic structures and early fibrosis diffusely involving liver tissues, whereas early fibrosis is challenging to be identified by conventional histopathological methods. Furthermore, the SHG emission directionality analysis revealed the maturation of each collagen fibre of each patient. As a result, SHG microscopy is feasible for assessing liver fibrosis on NAFLD patients, including the ultra-early stage of liver fibrosis that is difficult to diagnose by the conventional histopathological method. The assessment method of the ultra-early fibrosis by using SHG microscopy may serve as a crucial means for pathological, clinical, and prognostic diagnosis of NAFLD patients.

Liver fibrosis quantification

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

Intravital two-photon imaging and quantification of hepatic steatosis and fibrosis in a live small animal model

Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases closely associated with the metabolic system, including obesity and type 2 diabetes. The progression of NAFLD with advanced fibrosis is associated with an increased risk of liver cirrhosis and cancer as well as various extra-hepatic diseases. Yet, the underlying mechanism is not fully understood partly due to the absence of effective high-resolution in vivo imaging methods and the appropriate animal models recapitulating the pathology of NAFLD. To improve our understanding about complex pathophysiology of NAFLD, the need for an advanced imaging methodology to visualize and quantify subcellular-level features of NAFLD in vivo over time is ever-increasing. In this study, we established an advanced in vivo two-photon imaging technique to visualize and quantify subcellular-level pathological features of NAFLD in a live mouse animal developing hepatic steatosis, fibrosis, and disrupted microvasculature.

Label-Free Histology and Evaluation of Human Pancreatic Cancer with Coherent Nonlinear Optical Microscopy

Surgeries achieving maximal tumor resection remain the major effective treatment of pancreatic cancer. Rapid and precise intraoperative diagnosis of pancreatic tissues is critical for optimum surgical outcomes but is challenging for the current staining-based histological methods. We demonstrated that label-free coherent nonlinear optical microscopy with combined stimulated Raman scattering (SRS) and second harmonic generation (SHG) could reveal key diagnostic features of both normal and cancerous human pancreatic tissues. Adjacent pairs of tissue sections from resection margins of 37 patients were imaged by SRS and hematoxylin and eosin staining for direct comparison, demonstrating high diagnostic concordance (Cohen's kappa, κ > 0.97) between them. Fresh unprocessed tissues showed well-preserved histoarchitectures including pancreatic ducts, islets, acini, and nerves. Moreover, the area ratios of collagen fibers were analyzed and found to correlate with the drainage pancreatic amylase level (odds ratio = 28.0, p = 0.0017). Our results indicated that SRS/SHG histology provides potential for rapid intraoperative diagnosis of pancreatic cancer as well as a predictive value of postoperative pancreatic fistula.

Diet and exercise reduce pre-existing NASH and fibrosis and have additional beneficial effects on the vasculature, adipose tissue and skeletal muscle via organ-crosstalk

BACKGROUND

Non-alcoholic steatohepatitis (NASH) has become one of the most common liver diseases and is still without approved pharmacotherapy. Lifestyle interventions using exercise and diet change remain the current treatment of choice and even a small weight loss (5-7%) can already have a beneficial effect on NASH. However, the underlying molecular mechanisms of exercise and diet interventions remain largely elusive, and it is unclear whether they exert their health effects via similar or different pathways.

METHODS

Ldlr-/-.Leiden mice received a high fat diet (HFD) for 30 weeks to establish a severe state of NASH/fibrosis with simultaneous atherosclerosis development. Groups of mice were then either left untreated (control group) or were treated for 20 weeks with exercise (running wheel), diet change (switch to a low fat chow diet) or the combination thereof. The liver and distant organs including heart, white adipose tissue (WAT) and muscle were histologically examined. Comprehensive transcriptome analysis of liver, WAT and muscle revealed the organ-specific effects of exercise and diet and defined the underlying pathways.

RESULTS

Exercise and dietary change significantly reduced body weight, fat mass, adipocyte size and improved myosteatosis and muscle function with additive effects of combination treatment. WAT inflammation was significantly improved by diet change, tended to be reduced with exercise, and combination therapy had no additive effect. Hepatic steatosis and inflammation were almost fully reversed by exercise and diet change, while hepatic fibrosis tended to be improved with exercise and was significantly improved with diet change. Additive effects for the combination therapy were shown for liver steatosis and associated liver lipids, and atherosclerosis, but not for hepatic inflammation and fibrosis. Pathway analysis revealed complementary effects on metabolic pathways and lipid handling processes, thereby substantiating the added value of combined lifestyle treatment.

CONCLUSIONS

Exercise, diet change and the combination thereof can reverse established NASH/fibrosis in obese Ldlr-/-.Leiden mice. In addition, the lifestyle interventions had beneficial effects on atherosclerosis, WAT inflammation and muscle function. For steatosis and other parameters related to adiposity or lipid metabolism, exercise and dietary change affected more distinct pathways that acted complementary when the interventions were combined resulting in an additive effect for the combination therapy on important endpoints including NASH and atherosclerosis. For inflammation, exercise and diet change shared several underlying pathways resulting in a net similar effect when the interventions were combined.

Association of Tumor-Associated Collagen Signature With Prognosis and Adjuvant Chemotherapy Benefits in Patients With Gastric Cancer

IMPORTANCE

The current TNM staging system provides limited information for prognosis prediction and adjuvant chemotherapy benefits for patients with gastric cancer (GC).

OBJECTIVE

To develop a tumor-associated collagen signature of GC (TACSGC) in the tumor microenvironment to predict prognosis and adjuvant chemotherapy benefits in patients with GC.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study included a training cohort of 294 consecutive patients treated between January 1, 2012, and December 31, 2013, from Nanfang Hospital, Southern Medical University, People's Republic of China, and a validation cohort of 225 consecutive patients treated between October 1, 2010, and December 31, 2012, from Fujian Provincial Cancer Hospital, Fujian Medical University, People's Republic of China. In total, 146 collagen features in the tumor microenvironment were extracted with multiphoton imaging. A TACSGC was then constructed using the least absolute shrinkage and selection operator Cox proportional hazards regression model in the training cohort. Data analysis was conducted from October 1, 2020, to April 30, 2021.

MAIN OUTCOMES AND MEASURES

The association of TACSGC with disease-free survival (DFS) and overall survival (OS) was assessed. An independent external cohort was included to validate the results. Interactions between TACSGC and adjuvant chemotherapy were calculated.

RESULTS

This study included 519 patients (median age, 57 years [IQR, 49-65 years]; 360 [69.4%] male). A 9 feature-based TACSGC was built. A higher TACSGC level was significantly associated with worse DFS and OS in both the training (DFS: hazard ratio [HR], 3.57 [95% CI, 2.45-5.20]; OS: HR, 3.54 [95% CI, 2.41-5.20]) and validation (DFS: HR, 3.10 [95% CI, 2.26-4.27]; OS: HR, 3.24 [95% CI, 2.33-4.50]) cohorts (continuous variable, P < .001 for all comparisons). Multivariable analyses found that carbohydrate antigen 19-9, depth of invasion, lymph node metastasis, distant metastasis, and TACSGC were independent prognostic predictors of GC, and 2 integrated nomograms that included the 5 predictors were established for predicting DFS and OS. Compared with clinicopathological models that included only the 4 clinicopathological predictors, the integrated nomograms yielded an improved discrimination for prognosis prediction in a C index comparison (training cohort: DFS, 0.80 [95% CI, 0.73-0.88] vs 0.78 [95% CI, 0.71-0.85], P = .03; OS, 0.81 [95% CI, 0.75-0.88] vs 0.80 [95% CI, 0.73-0.86], P = .03; validation cohort: DFS, 0.78 [95% CI, 0.70-0.87] vs 0.76 [95% CI, 0.67-0.84], P = .006; OS, 0.78 [95% CI, 0.69-0.86] vs 0.75 [95% CI, 0.67-0.84], P = .002). Patients with stage II and III GC and low TACSGC levels rather than high TACSGC levels had a favorable response to adjuvant chemotherapy (DFS: HR, 0.65 [95% CI, 0.43-0.96]; P = .03; OS: HR, 0.55 [95% CI, 0.36-0.82]; P = .004; dichotomized variable, P < .001 for interaction for both comparisons).

CONCLUSIONS AND RELEVANCE

The findings suggest that TACSGC provides additional prognostic information for patients with GC and may distinguish patients with stage II and III disease who are more likely to derive benefits from adjuvant chemotherapy.

A human multi-lineage hepatic organoid model for liver fibrosis

To investigate the pathogenesis of a congenital form of hepatic fibrosis, human hepatic organoids were engineered to express the most common causative mutation for Autosomal Recessive Polycystic Kidney Disease (ARPKD). Here we show that these hepatic organoids develop the key features of ARPKD liver pathology (abnormal bile ducts and fibrosis) in only 21 days. The ARPKD mutation increases collagen abundance and thick collagen fiber production in hepatic organoids, which mirrors ARPKD liver tissue pathology. Transcriptomic and other analyses indicate that the ARPKD mutation generates cholangiocytes with increased TGFβ pathway activation, which are actively involved stimulating myofibroblasts to form collagen fibers. There is also an expansion of collagen-producing myofibroblasts with markedly increased PDGFRB protein expression and an activated STAT3 signaling pathway. Moreover, the transcriptome of ARPKD organoid myofibroblasts resemble those present in commonly occurring forms of liver fibrosis. PDGFRB pathway involvement was confirmed by the anti-fibrotic effect observed when ARPKD organoids were treated with PDGFRB inhibitors. Besides providing insight into the pathogenesis of congenital (and possibly acquired) forms of liver fibrosis, ARPKD organoids could also be used to test the anti-fibrotic efficacy of potential anti-fibrotic therapies.

Reliable computational quantification of liver fibrosis is compromised by inherent staining variation

Biopsy remains the gold-standard measure for staging liver disease, both to inform prognosis and to assess the response to a given treatment. Semiquantitative scores such as the Ishak fibrosis score are used for evaluation. These scores are utilised in clinical trials, with the US Food and Drug Administration mandating particular scores as inclusion criteria for participants and using the change in score as evidence of treatment efficacy. There is an urgent need for improved, quantitative assessment of liver biopsies to detect small incremental changes in liver architecture over the course of a clinical trial. Artificial intelligence (AI) methods have been proposed as a way to increase the amount of information extracted from a biopsy and to potentially remove bias introduced by manual scoring. We have trained and evaluated an AI tool for measuring the amount of scarring in sections of picrosirius red-stained liver. The AI methodology was compared with both manual scoring and widely available colour space thresholding. Four sequential sections from each case were stained on two separate occasions by two independent clinical laboratories using routine protocols to study the effect of inter- and intra-laboratory staining variation on these tools. Finally, we compared these methods to second harmonic generation (SHG) imaging, a stain-free quantitative measure of collagen. Although AI methods provided a modest improvement over simpler computer-assisted measures, staining variation both within and between laboratories had a dramatic effect on quantitation, with manual assignment of scar proportion being the most consistent. Manual assessment also most strongly correlated with collagen measured by SHG. In conclusion, results suggest that computational measures of liver scarring from stained sections are compromised by inter- and intra-laboratory staining. Stain-free quantitative measurement using SHG avoids staining-related variation and may prove more accurate in detecting small changes in scarring that may occur in therapeutic trials.

Optical Microscopy and the Extracellular Matrix Structure: A Review

Biological tissues are not uniquely composed of cells. A substantial part of their volume is extracellular space, which is primarily filled by an intricate network of macromolecules constituting the extracellular matrix (ECM). The ECM serves as the scaffolding for tissues and organs throughout the body, playing an essential role in their structural and functional integrity. Understanding the intimate interaction between the cells and their structural microenvironment is central to our understanding of the factors driving the formation of normal versus remodelled tissue, including the processes involved in chronic fibrotic diseases. The visualization of the ECM is a key factor to track such changes successfully. This review is focused on presenting several optical imaging microscopy modalities used to characterize different ECM components. In this review, we describe and provide examples of applications of a vast gamut of microscopy techniques, such as widefield fluorescence, total internal reflection fluorescence, laser scanning confocal microscopy, multipoint/slit confocal microscopy, two-photon excited fluorescence (TPEF), second and third harmonic generation (SHG, THG), coherent anti-Stokes Raman scattering (CARS), fluorescence lifetime imaging microscopy (FLIM), structured illumination microscopy (SIM), stimulated emission depletion microscopy (STED), ground-state depletion microscopy (GSD), and photoactivated localization microscopy (PALM/fPALM), as well as their main advantages, limitations.

Evolution of the liver biopsy and its future

Liver biopsies are commonly used to evaluate a wide variety of medical disorders, including neoplasms and post-transplant complications. However, its use is being impacted by improved clinical diagnosis of disorders, and non-invasive methods for evaluating liver tissue and as a result the indications of a liver biopsy have undergone major changes in the last decade. The evolution of highly effective treatments for some of the common indications for liver biopsy in the last decade (e.g., viral hepatitis B and C) has led to a decline in the number of liver biopsies in recent years. At the same time, the emergence of better technologies for histologic evaluation, tissue content analysis and genomics are among the many new and exciting developments in the field that hold great promise for the future and are going to shape the indications for a liver biopsy in the future. Recent advances in slide scanners now allow creation of "digital/virtual" slides that have image of the entire tissue section present in a slide [whole slide imaging (WSI)]. WSI can now be done very rapidly and at very high resolution, allowing its use in routine clinical practice. In addition, a variety of technologies have been developed in recent years that use different light sources and/or microscopes allowing visualization of tissues in a completely different way. One such technique that is applicable to liver specimens combines multiphoton microscopy (MPM) with advanced clearing and fluorescent stains known as Clearing Histology with MultiPhoton Microscopy (CHiMP). Although it has not yet been extensively validated, the technique has the potential to decrease inefficiency, reduce artifacts, and increase data while being readily integrable into clinical workflows. Another technology that can provide rapid and in-depth characterization of thousands of molecules in a tissue sample, including liver tissues, is matrix assisted laser desorption/ionization (MALDI) mass spectrometry. MALDI has already been applied in a clinical research setting with promising diagnostic and prognostic capabilities, as well as being able to elucidate mechanisms of liver diseases that may be targeted for the development of new therapies. The logical next step in huge data sets obtained from such advanced analysis of liver tissues is the application of machine learning (ML) algorithms and application of artificial intelligence (AI), for automated generation of diagnoses and prognoses. This review discusses the evolving role of liver biopsies in clinical practice over the decades, and describes newer technologies that are likely to have a significant impact on how they will be used in the future.

Second-harmonic generation (SHG) microscopy and hepatic venous pressure gradient-based validation of a novel histological staging system for alcoholic hepatitis

Alcoholic hepatitis (AH) lacks specific histological staging. A novel fibrosis staging that encompasses perisinusoidal fibrosis and cirrhosis sub-stages, substantiated by Hepatic venous pressure gradient (HVPG) and automated fibrosis quantification, is imperative. To correlate novel histological staging system of AH with second-harmonic generation microscopy (SHG)-based q-fibrosis, HVPG, and activated hepatic stellate cells (HSCs). Liver biopsies of AH (n = 175) were staged semi-quantitatively as F0, F1, F2, F3A and F3B and Laennec substages of cirrhosis 4A, 4B and 4C. Stages were correlated with SHG q-fibrosis parameters, HVPG and HSCs. Mean age 41.2 ± 9.4 years, 96.6% males, bilirubin 20.58 ± 8.0 mg/dl and Maddrey's discriminant function 78.9 ± 36.7 displayed advanced fibrosis in 98.6%. With increasing histological stages, an increase in q-fibrosis indices and mean HVPG (p < 0.0001) were recorded; stage 4C showed the most significant difference from other stages (p < 0.000). Stages 3A and 3B were comparable with the stages 4A and 4B, respectively, for q-fibrosis (p = 1) and HVPG (p = 1). HSCs (> 30%) were significantly higher in stage 3 (75%) compared with 4 (49%) and 2 (59%), p = 0.018. Overall agreement for histological staging was excellent for all stages (0.82). SHG quantified fibrosis and HVPG corroborates the novel histological staging of AH. Expansive PCF matches with collagen content and clinical severity to early sub-stages of cirrhosis. This highlights the need for an accurate quantification and inclusion of PCF as a separate stage. SHG-based quantification can be a useful adjunct to histological fibrosis staging systems.

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.

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

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

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.

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

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

Prognostic value of tumor stromal collagen features in patients with hepatocellular carcinoma revealed by second-harmonic generation microscopy

INTRODUCTION

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide. The search for new biomarkers that predict the outcome of HCC patients is ongoing. We propose the second harmonic generation-based quantitative assessment approach to evaluate the prognostic value of tumor stromal collagen in HCC.

MATERIALS AND METHODS

We evaluated tumor stromal collagen in paraffin-embedded specimens from 109 HCC patients by second-harmonic generation imaging. The parameters and quantitative assessment of collagen were obtained using a fiber network extraction algorithm. The relationships between collagen features and clinical pathological features and overall survival were statistically analyzed.

RESULT

Among the collagen features, some parameters of aggregated collagen correlated well with clinical pathological features, especially the aggregated collagen cross-linked density. Cross-linked collagen fibers form a fiber network in moderately and poor differentiated HCCs. Kaplan-Meier analyses and the multivariate Cox proportional hazard model showed that high aggregated collagen cross-linked density was associated with poor overall survival. The chi-squared test showed that aggregated cross-link density was significantly associated with histological grade and tumor recurrence.

CONCLUSION

Our results indicate the prognostic value of the quantitative evaluation of tumor stromal collagen using second harmonic generation imaging of patients with HCC.

Multiphoton Microscopic Study of the Renal Cell Carcinoma Pseudocapsule: Implications for Tumour Enucleation

OBJECTIVE

To utilize Multiphoton Microscopy (MPM) as a novel imaging technique to characterize and quantify collagen at the Renal Cell Carcinoma Pseudocapsule, to assess for both intra-tumoral and inter-tumoral variation of collagen characteristics. MPM combines Second Harmonic Generation and Two Photon Excitation Fluorescence to image extracellular matrix architecture.

METHODS

Twenty partial nephrectomy specimen tissues were retrieved, cut into 5-micron sections, mounted on slides and deparaffinized. The pseudocapsules (PCs) were imaged with 2X and 20X objective at selected Regions of Interest. Corresponding clinical information was retrieved. PC thickness was determined. Collagen parameters measured included quantification by the Collagen Area Ratio, and qualitative measurements by the Collagen Fiber Density and Collagen Reticulation Index.

RESULTS

The boundaries between tumor, PC and normal renal parenchyma were distinguished by MPM without need for staining. In the thickest areas of the PC, collagen content and density were quantitatively higher compared to the thinnest areas. Median Collagen Area Ratio was higher in the thickest compared to the thinnest areas of the PC (P = .01). Clear Cell RCC specimens had a consistently higher Collagen Fiber Density in both the thickest and thinnest areas compared to non-Clear Cell RCC specimens (P = .02).

CONCLUSIONS

We demonstrated the ability of MPM to quantify collagen characteristics of PCs without fluorescent labeling. Tumor enucleation for Renal Cell Carcinoma along its PC remains debatable with regards to oncological safety. Even with a complete and intact PC, the PC is not a homogenous structure, and varies in its thickness and its collagen characteristics within, and between tumors.

Label-free characterization of collagen fibers in cancerous esophagus tissues using ratiometric nonlinear optical microscopy

IMPACT STATEMENT

The issue of classifying esophageal cancer at various developmental stages is crucial for determining the optimized treatment protocol for the patients, as well as the prognosis. Precision improvement in staging esophageal cancer keeps seeking quantitative and analytical imaging methods that could augment histopathological techniques. In this work, we used nonlinear optical microscopy for ratiometric analysis on the intrinsic signal of two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) from single collagen fibers only in submucosa of esophageal squamous cell carcinoma (ESCC). The blind tests of TPEF/SHG and forward (F)/backward (B) SHG were demonstrated to compare with the histology conclusion. The discussion of sensitivity and specificity was provided via statistical comparison between the four stages of esophageal cancer. To the best of our knowledge, this is the first study of using these two ratios in combination for staging ESCC.

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.

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.

Intensity-based registration of bright-field and second-harmonic generation images of histopathology tissue sections

The use of second-harmonic generation (SHG) microscopy in biomedical research is rapidly increasing. This is due in large part to the wide spread interest of using this imaging technique to examine the role of fibrillar collagen organization in diseases such as cancer. The co-examination of SHG images and traditional bright-field (BF) images of hematoxylin and eosin (H&E) stained tissue as a gold standard clinical validation is usually required. However, image registration of these two modalities has been mostly done by manually selecting corresponding landmarks which is labor intensive and error prone. We designed, implemented, and validated the first image intensity-based registration method capable of automatically aligning SHG images and BF images. In our algorithmic approach, a feature extractor is used to pre-process the BF image to block the content features not visible in SHG images and the output image is then aligned with the SHG image by maximizing the common image features. An alignment matrix maximizing the image mutual information is found by evolutionary optimization and the optimization is facilitated using a hierarchical multiresolution framework. The automatic registration results were compared to traditional manual registration to assess the performance of the algorithm. The proposed algorithm has been successfully used in several biomedical studies such as pancreatic and kidney cancer studies and shown great efficacy.

Campagnola P. Imaging Collagen Alterations in STICs and High Grade Ovarian Cancers in the Fallopian Tubes by Second Harmonic Generation Microscopy

The majority of high-grade serous ovarian cancers originate in the fallopian tubes, however, the corresponding structural changes in the extracellular matrix (ECM) have not been well-characterized. This information could provide new insight into the carcinogenesis and provide the basis for new diagnostic tools. We have previously used the collagen-specific Second Harmonic Generation (SHG) microscopy to probe collagen fiber alterations in high-grade serous ovarian cancer and in other ovarian tumors, and showed they could be uniquely identified by machine learning approaches. Here we couple SHG imaging of serous tubal intra-epithelial carcinomas (STICs), high-grade cancers, and normal regions of the fallopian tubes, using three distinct image analysis approaches to form a classification scheme based on the respective collagen fiber morphology. Using a linear discriminant analysis, we achieved near 100% classification accuracy between high-grade disease and the other tissues, where the STICs and normal regions were differentiated with ~75% accuracy. Importantly, the collagen in high-grade disease in both the fallopian tube and the ovary itself have a similar collagen morphology, further substantiating the metastasis between these sites. This analysis provides a new method of classification, but also quantifies the structural changes in the disease, which may provide new insight into metastasis.

A novel nutritional supplement prevents muscle loss and accelerates muscle mass recovery in caloric-restricted mice

BACKGROUND

Muscle atrophy is defined as decreased muscle mass, associated with aging as well as with various chronic diseases and is a fundamental cause of frailty, functional decline and disability. Frailty represents a huge potential public health issue worldwide with high impact on healthcare costs. A major clinical issue is therefore to devise new strategies preventing muscle atrophy. In this study, we tested the efficacy of Vital01, a novel oral nutritional supplement (ONS), on body weight and muscle mass using a caloric restriction-induced mouse model for muscle atrophy.

METHODS

Mice were calorically restricted for 2 weeks to induce muscle atrophy: one control group received 60% kcal of the normal chow diet and one intervention group received 30% kcal chow and 30 kcal% Vital01. The effects on body weight, lean body mass, muscle histology and transcriptome were assessed. In addition, the effects of Vital01, in mice with established muscle atrophy, were assessed and compared to a standard ONS. To this end, mice were first calorically restricted on a 60% kcal chow diet and then refed with either 100 kcal% chow, a mix of Vital01 (receiving 60% kcal chow and 40 kcal% Vital01) or with a mix of standard, widely prescribed ONS (receiving 60 kcal% chow and 40 kcal% Fortisip Compact).

RESULTS

Vital01 attenuated weight loss (-15% weight loss for Vital01 vs. -25% for control group, p < 0.01) and loss of muscle mass (Vital01 with -13%, -12% and -18%, respectively, for gastrocnemius, quadriceps and tibialis vs. 25%, -23% and -28%, respectively, for control group, all p < 0.05) and also restored body weight, fat and muscle mass more efficiently when compared to Fortisip Compact. As assessed by transcriptome analysis and Western blotting of key proteins (e.g. phospoAKT, mTOR and S6K), Vital01 attenuated the catabolic and anabolic signaling pathways induced by caloric restriction and modulated inflammatory and mitochondrial pathways. In addition, Vital01 affected pathways related to matrix proteins/collagens homeostasis and tended to reduce caloric restriction-induced collagen fiber density in the quadriceps (with -27%, p = 0.051).

CONCLUSIONS

We demonstrate that Vital01 preserves muscle mass in a calorically restricted mouse model for muscle atrophy. Vital01 had preventive effects when administered during development of muscle atrophy. Furthermore, when administered in a therapeutic setting to mice with established muscle atrophy, Vital01 rapidly restored body weight and accelerated the recurrence of fat and lean body mass more efficiently than Fortisip Compact. Bioinformatics analysis of gene expression data identified regulatory pathways that were specifically influenced by Vital01 in muscle.

Collagen organization of renal cell carcinoma differs between low and high grade tumors

Background

The traditional pathologic grading for human renal cell carcinoma (RCC) has low concordance between biopsy and surgical specimen. There is a need to investigate adjunctive pathology technique that does not rely on the nuclear morphology that defines the traditional grading. Changes in collagen organization in the extracellular matrix have been linked to prognosis or grade in breast, ovarian, and pancreatic cancers, but collagen organization has never been correlated with RCC grade. In this study, we used Second Harmonic Generation (SHG) based imaging to quantify possible differences in collagen organization between high and low grades of human RCC.

Methods

A tissue microarray (TMA) was constructed from RCC tumor specimens. Each TMA core represents an individual patient. A 5 μm section from the TMA tissue was stained with standard hematoxylin and eosin (H&E). Bright field images of the H&E stained TMA were used to annotate representative RCC regions. In this study, 70 grade 1 cores and 51 grade 4 cores were imaged on a custom-built forward SHG microscope, and images were analyzed using established software tools to automatically extract and quantify collagen fibers for alignment and density assessment. A linear mixed-effects model with random intercepts to account for the within-patient correlation was created to compare grade 1 vs. grade 4 measurements and the statistical tests were two-sided.

Results

Both collagen density and alignment differed significantly between RCC grade 1 and RCC grade 4. Specifically, collagen fiber density was greater in grade 4 than in grade 1 RCC (p < 0.001). Collagen fibers were also more aligned in grade 4 compared to grade 1 (p < 0.001).

Conclusions

Collagen density and alignment were shown to be significantly higher in RCC grade 4 vs. grade 1. This technique of biopsy sampling by SHG could complement classical tumor grading approaches. Furthermore it might allow biopsies to be more clinically relevant by informing diagnostics. Future studies are required to investigate the functional role of collagen organization in RCC.

Quantification of hepatic steatosis in chronic liver disease using novel automated method of second harmonic generation and two-photon excited fluorescence

The presence of hepatic steatosis (HS) is an important histological feature in a variety of liver disease. It is critical to assess HS accurately, particularly where it plays an integral part in defining the disease. Conventional methods of quantifying HS remain semi-quantitative, with potential limitations in precision, accuracy and subjectivity. Second Harmonic Generation (SHG) microscopy is a novel technology using multiphoton imaging techniques with applicability in histological tissue assessment. Using an automated algorithm based on signature SHG parameters, we explored the utility and application of SHG for the diagnosis and quantification of HS. SHG microscopy analysis using GENESIS (HistoIndex, Singapore) was applied on 86 archived liver biopsy samples. Reliability was correlated with 3 liver histopathologists. Data analysis was performed using SPSS. There was minimal inter-observer variability between the 3 liver histopathologists, with an intraclass correlation of 0.92 (95% CI 0.89–0.95; p < 0.001). Good correlation was observed between the histopathologists and automated SHG microscopy assessment of HS with Pearson correlation of 0.93: p < 0.001. SHG microscopy provides a valuable tool for objective, more precise measure of HS using an automated approach. Our study reflects proof of concept evidence for potential future refinement to current conventional histological assessment.

Fractal dimension and directional analysis of elastic and collagen fiber arrangement in unsectioned arterial tissues affected by atherosclerosis and aging

Structural proteins like collagen and elastin are major constituents of the extracellular matrix (ECM). ECM degradation and remodeling in diseases significantly impact the microorganization of these structural proteins. Therefore, tracking the changes of collagen and elastin fiber morphological features within ECM impacted by disease progression could provide valuable insight into pathological processes such as tissue fibrosis and atherosclerosis. Benefiting from its intrinsic high-resolution imaging power and superior biochemical specificity, nonlinear optical microscopy (NLOM) is capable of providing information critical to the understanding of ECM remodeling. In this study, alterations of structural fibrillar proteins such as collagen and elastin in arteries excised from atherosclerotic rabbits were assessed by the combination of NLOM images and textural analysis methods such as fractal dimension (FD) and directional analysis (DA). FD and DA were tested for their performance in tracking the changes of extracellular elastin and fibrillar collagen remodeling resulting from atherosclerosis progression/aging. Although other methods of image analysis to study the organization of elastin and collagen structures have been reported, the simplified calculations of FD and DA presented in this work prove that they are viable strategies for extracting and analyzing fiber-related morphology from disease-impacted tissues. Furthermore, this study also demonstrates the potential utility of FD and DA in studying ECM remodeling caused by other pathological processes such as respiratory diseases, several skin conditions, or even cancer. NEW & NOTEWORTHY Textural analyses such as fractal dimension (FD) and directional analysis (DA) are straightforward and computationally viable strategies to extract fiber-related morphological data from optical images. Therefore, objective, quantitative, and automated characterization of protein fiber morphology in extracellular matrix can be realized by using these methods in combination with digital imaging techniques such as nonlinear optical microscopy (NLOM), a highly effective visualization tool for fibrillar collagen and elastic network. Combining FD and DA with NLOM is an innovative approach to track alterations of structural fibrillar proteins. The results illustrated in this study not only prove the effectiveness of FD and DA methods in extracellular protein characterization but also demonstrate their potential value in clinical and basic biomedical research where protein microstructure characterization is critical.

Tissue Intrinsic Fluorescence Spectra-Based Digital Pathology of Liver Fibrosis by Marker-Controlled Segmentation

Tissue intrinsic emission fluorescence provides useful diagnostic information for various diseases. Because of its unique feature of spectral profiles depending on tissue types, spectroscopic imaging is a promising tool for accurate evaluation of endogenous fluorophores. However, due to difficulties in discriminating those sources, quantitative analysis remains challenging. In this study, we quantitatively investigated spectral-spatial features of multi-photon excitation fluorescence in normal and diseased livers. For morphometrics of multi-photon excitation spectra, we examined a marker-controlled segmentation approach and its application to liver fibrosis assessment by employing a mouse model of carbon tetrachloride (CCl₄)-induced liver fibrosis. We formulated a procedure of internal marker selection where markers were chosen to reflect typical biochemical species in the liver, followed by image segmentation and local morphological feature extraction. Image segmentation enabled us to apply mathematical morphology analysis, and the local feature was applied to the automated classification test based on a machine learning framework, both demonstrating highly accurate classifications. Through the analyses, we showed that spectral imaging of native fluorescence from liver tissues have the capability of differentiating not only between normal and diseased, but also between progressive disease states. The proposed approach provides the basics of spectroscopy-based digital histopathology of chronic liver diseases, and can be applied to a range of diseases associated with autofluorescence alterations.

Obeticholic Acid Modulates Serum Metabolites and Gene Signatures Characteristic of Human NASH and Attenuates Inflammation and Fibrosis Progression in Ldlr-/-.Leiden Mice

Concerns have been raised about whether preclinical models sufficiently mimic molecular disease processes observed in nonalcoholic steatohepatitis (NASH) patients, bringing into question their translational value in studies of therapeutic interventions in the process of NASH/fibrosis. We investigated the representation of molecular disease patterns characteristic for human NASH in high-fat diet (HFD)-fed Ldlr-/-.Leiden mice and studied the effects of obeticholic acid (OCA) on these disease profiles. Multiplatform serum metabolomic profiles and genome-wide liver transcriptome from HFD-fed Ldlr-/-.Leiden mice were compared with those of NASH patients. Mice were profiled at the stage of mild (24 weeks HFD) and severe (34 weeks HFD) fibrosis, and after OCA intervention (24-34 weeks; 10 mg/kg/day). Effects of OCA were analyzed histologically, biochemically, by immunohistochemistry, using deuterated water technology (de novo collagen formation), and by its effect on the human-based transcriptomics and metabolomics signatures. The transcriptomics and metabolomics profile of Ldlr-/-.Leiden mice largely reflected the molecular signature of NASH patients. OCA modulated the expression of these molecular profiles and quenched specific proinflammatory-profibrotic pathways. OCA attenuated specific facets of cellular inflammation in liver (F4/80-positive cells) and reduced crown-like structures in adipose tissue. OCA reduced de novo collagen formation and attenuated further progression of liver fibrosis, but did not reduce fibrosis below the level before intervention. Conclusion: HFD-fed Ldlr-/-.Leiden mice recapitulate molecular transcriptomic and metabolomic profiles of NASH patients, and these signatures are modulated by OCA. Intervention with OCA in developing fibrosis reduces collagen deposition and de novo synthesis but does not resolve already manifest fibrosis in the period studied. These data show that human molecular signatures can be used to evaluate the translational character of preclinical models for NASH.

MMP-9 inhibition promotes anti-tumor immunity through disruption of biochemical and physical barriers to T-cell trafficking to tumors

Matrix metalloproteinase-9 (MMP-9), whose expression is frequently dysregulated in cancer, promotes tumor growth, invasion, and metastasis by multiple mechanisms, including extracellular matrix remodeling and growth-factor and cytokine activation. We developed a monoclonal antibody against murine MMP-9, which we found decreased growth of established primary tumors in an orthotopic model of HER2-driven breast cancer (HC11-NeuT) in immunocompetent mice. RNA sequencing (RNAseq) profiling of NeuT tumors and additional mouse model tumors revealed that anti-MMP-9 treatment resulted in upregulation of immune signature pathways associated with cytotoxic T-cell response. As there is a need to boost the low response rates observed with anti-PDL1 antibody treatment in the clinical setting, we assessed the potential of anti-MMP-9 to improve T-cell response to immune checkpoint inhibitor anti-PDL1 in NeuT tumors. Anti-MMP-9 and anti-PDL1 cotreatment reduced T-cell receptor (TCR) clonality and increased TCR diversity, as detected by TCR sequencing of NeuT tumors. Flow cytometry analyses of tumors showed that the combination treatment increased the frequency of CD3+ T cells, including memory/effector CD4 and CD8 T cells, but not regulatory T cells, among tumor-infiltrating leukocytes. Moreover, in vitro enzymatic assays corroborated that MMP-9 cleaves key T-cell chemoattractant CXC receptor 3 ligands (CXC ligand [CXCL] 9, CXCL10, and CXCL11) and renders them inactive in T-cell migration assays. Consistent with our in vitro experiments, analysis of NeuT tumor protein lysates showed that anti-MMP-9 treatment increases expression of CXCL10 and other T cell–stimulating factors, such as interleukin (IL)-12p70 and IL-18. We show that inhibition of MMP-9, a key component of the tumor-promoting and immune-suppressive myeloid inflammatory milieu, increases T-helper cell 1 type cytokines, trafficking of effector/memory T cells into tumors, and intratumoral T-cell diversity.