Fibro-C-Index: comprehensive, morphology-based quantification of liver fibrosis using second harmonic generation and two-photon microscopy

Liver fibrosis showed a two-phase regression rate during long-term anti-HBV therapy by three-time biopsies assessments

BACKGROUND

Evidence has proven that liver fibrosis or even cirrhosis can be reversed by anti-HBV treatment. However, the difference of fibrosis regression rates in short-term and long-term antiviral therapy remain unclear. Therefore, we aimed to identify the dynamic changes in fibrosis regression rate in patients with three-time liver biopsies during 5 years antiviral therapy.

METHODS

CHB patients with three times of liver biopsies (baseline, after 1.5-year and 5-year antiviral therapy) from a prospective cohort were enrolled. All patients were biopsy-proved Ishak stage ≥ 3 at baseline (n = 92). Fibrosis regression was defined as Ishak stage decreased ≥ 1 or predominantly regressive categorized by P-I-R score.

RESULTS

Totals of 65.2% (60/92) and 80.4% (74/92) patients attained fibrosis regression after 1.5-year and 5-year therapy, respectively. Median HBV DNA level declined from 6.5 log IU/ml (baseline) to 0 log IU/ml (1.5 years and 5 years, P < 0.001). The mean level of Ishak fibrosis stage in all patients decreased from stage 4.1 (baseline) to 3.7 (1.5 years) then 3.2 (5 years). Fibrosis regression rates were 0.27 stage/year between baseline to year 1.5 and 0.14 stage/year between year 1.5 and year 5. Furthermore, for patients who attained fibrosis regression after 5-year antiviral therapy, the two-phase regression rates were 0.39 stage/year (0 year-1.5 years) and 0.20 stage/year (1.5 years-5 years). This two-phase feature of regression rate was further confirmed by fully-quantification assessment of liver fibrosis based on SHG/TPEF.

CONCLUSION

During the 5 years of long-term antiviral treatment, liver fibrosis rapidly regresses in the first 1.5 years before slowing down in the following 3.5 years.

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.

Quantitative Assessment of Hepatic Steatosis Using Label-Free Multiphoton Imaging and Customized Image Processing Program

Nonalcoholic fatty liver disease is rapidly becoming one of the most common causes of chronic liver disease worldwide and is the leading cause of liver-related morbidity and mortality. A quantitative assessment of the degree of steatosis would be more advantageous for diagnostic evaluation and exploring the patterns of disease progression. Here, multiphoton microscopy, based on the second harmonic generation and 2-photon excited fluorescence, was used to label-free image the samples of nonalcoholic fatty liver. Imaging results confirm that multiphoton microscopy is capable of directly visualizing important pathologic features such as normal hepatocytes, hepatic steatosis, Mallory bodies, necrosis, inflammation, collagen deposition, microvessel, and so on and is a reliable auxiliary tool for the diagnosis of nonalcoholic fatty liver disease. Furthermore, we developed an image segmentation algorithm to simultaneously assess hepatic steatosis and fibrotic changes, and quantitative results reveal that there is a correlation between the degree of steatosis and collagen content. We also developed a feature extraction program to precisely display the spatial distribution of hepatocyte steatosis in tissues. These studies may be beneficial for a better clinical understanding of the process of steatosis as well as for exploring possible therapeutic targets.

Diagnosis of liver diseases based on artificial intelligence

Due to a series of problems in the diagnosis of liver disease, the mortality rate of liver disease patients is very high. Therefore, it is necessary for doctors and researchers to find a more effective non-invasive diagnostic method to meet clinical needs. We analyzed data from 416 patients with liver disease and 167 patients without liver disease from northeastern Andhra Pradesh, India. On the basis of considering age, gender and other basic data of patients, this paper uses total bilirubin and other clinical data as parameters to build a diagnostic model. In this paper, the accuracy of artificial intelligence method Random Forest (RF) and Support Vector Machine (SVM) model in the diagnosis of liver patients was compared. The results show that the support vector machine model based on Gaussian kernel function is more excellent in diagnostic accuracy, that is, SVM method is more suitable for the diagnosis of liver diseases.

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.

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.

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.

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.

Predict Early Recurrence of Resectable Hepatocellular Carcinoma Using Multi-Dimensional Artificial Intelligence Analysis of Liver Fibrosis

Simple Summary

Hepatocellular carcinoma (HCC) is the third most commonly diagnosed cancer in the world, and surgical resection is the commonly used curative management of early-stage disease. However, the recurrence rate is high after resection, and liver fibrosis has been thought to increase the risk of recurrence. Conventional histological staging of fibrosis is highly subjective to observer variations. To overcome this limitation, we used a fully quantitative fibrosis assessment tool, qFibrosis (utilizing second harmonic generation and two-photon excitation fluorescence microscopy), with multi-dimensional artificial intelligence analysis to establish a fully-quantitative, accurate fibrotic score called a “combined index”, which can predict early recurrence of HCC after curative intent resection. Therefore, we can pay more attention on the patients with high risk of early recurrence.

Abstract

Background: Liver fibrosis is thought to be associated with early recurrence of hepatocellular carcinoma (HCC) after resection. To recognize HCC patients with higher risk of early recurrence, we used a second harmonic generation and two-photon excitation fluorescence (SHG/TPEF) microscopy to create a fully quantitative fibrosis score which is able to predict early recurrence. Methods: The study included 81 HCC patients receiving curative intent hepatectomy. Detailed fibrotic features of resected hepatic tissues were obtained by SHG/TPEF microscopy, and we used multi-dimensional artificial intelligence analysis to create a recurrence prediction model “combined index” according to the morphological collagen features of each patient’s non-tumor hepatic tissues. Results: Our results showed that the “combined index” can better predict early recurrence (area under the curve = 0.917, sensitivity = 81.8%, specificity = 90.5%), compared to alpha fetoprotein level (area under the curve = 0.595, sensitivity = 68.2%, specificity = 47.6%). Using a Cox proportional hazards analysis, a higher “combined index” is also a poor prognostic factor of disease-free survival and overall survival. Conclusions: By integrating multi-dimensional artificial intelligence and SHG/TPEF microscopy, we may locate patients with a higher risk of recurrence, follow these patients more carefully, and conduct further management if needed.

Comparing hepatic steatosis distribution patterns between non-alcoholic fatty liver disease and fatty liver disease with chronic hepatitis B by second-harmonic generation/two-photon excited fluorescence method

INTRODUCTION AND OBJECTIVES

Hepatitis B virus (HBV) might be an etiological factor modulating fat distribution in steatotic livers. We aim to compare hepatic steatosis distribution patterns between NAFLD and FL&CHB patients with second-harmonic generation (SHG)/two-photon excited fluorescence (TPEF) method.

PATIENTS AND METHODS

42 patients with NAFLD, 46 with FL&CHB and 55 without steatosis were enrolled in the study. Overall and regional steatosis in liver sections were quantified by SHG/TPEF method. The accuracy of which was validated by pathologist evaluation and magnetic resonance spectroscopy (MRS). Difference in degree of overall and regional steatosis between NAFLD and FL&CHB groups was analyzed by Mann-Whitney U test. Multivariable linear regression analysis was used to model factors contributing to steatosis distribution.

RESULTS

The hepatic steatosis measured by SHG/TPEF method was highly correlated with pathologist grading (r=0.83, p<0.001) and MRS measurement (r=0.82, p<0.001). The level of overall steatosis in FL&CHB group is significantly lower than that in NAFLD group (p<0.001). In NAFLD group, periportal region has significantly lower steatosis percentage than lobule region and overall region (p<0.001); while in FL&CHB group there is no difference among regions. The ratio of steatosis at periportal region to lobule region is significantly higher in FL&CHB group than that in NAFLD group (p<0.05). Multivariable linear regression analysis shows that HBV infection is the major contributing factor (β=0.322, p<0.01).

CONCLUSIONS

SHG/TPEF method is an accurate and objective method in hepatic steatosis quantification. By quantifying steatosis in different histological regions, we found steatosis distribution patterns are different between FL&CHB and NAFLD patients.

Characterization of fibrillar collagen isoforms in infarcted mouse hearts using second harmonic generation imaging

We utilized collagen specific second harmonic generation (SHG) signatures coupled with correlative immunofluorescence imaging techniques to characterize collagen structural isoforms (type I and type III) in a murine model of myocardial infarction (MI). Tissue samples were imaged over a four week period using SHG, transmitted light microscopy and immunofluorescence imaging using fluorescently-labeled collagen antibodies. The post-mortem cardiac tissue imaging using SHG demonstrated a progressive increase in collagen deposition in the left ventricle (LV) post-MI. We were able to monitor structural morphology and LV remodeling parameters in terms of extent of LV dilation, stiffness and fiber dimensions in the infarcted myocardium.

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.

Assessment of progressive alterations in collagen organization in the postoperative conjunctiva by multiphoton microscopy

Glaucoma filtration surgery (GFS) commonly fails due to excessive fibrosis. As collagen structure aberrations is implicated in adverse fibrotic progression, this study aims to uncover collagen organization alterations during postoperative scarring. Via quantitative second harmonic generation/two photon excitation multiphoton imaging, we reveal the scar development and phenotype in the mouse model of conjunctival scarring. We also show that multiphoton imaging corroborated the collagen ultrastructure anomaly characteristic of the SPARC-/- mouse postoperative conjunctiva. These data improve our understanding of postoperative conjunctival scarring and further enhance the utility of this model for the development of anti-fibrotic therapeutics for GFS.

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.

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.

Recent advances in multiphoton microscopy combined with nanomaterials in the field of disease evolution and clinical applications to liver cancer

Multiphoton microscopy (MPM) is expected to become a powerful clinical tool, with its unique advantages of being label-free, high resolution, deep imaging depth, low light photobleaching and low phototoxicity. Nanomaterials, with excellent physical and chemical properties, are biocompatible and easy to prepare and functionalize. The addition of nanomaterials exactly compensates for some defects of MPM, such as the weak endogenous signal strength, limited imaging materials, insufficient imaging depth and lack of therapeutic effects. Therefore, combining MPM with nanomaterials is a promising biomedical imaging method. Here, we mainly review the principle of MPM and its application in liver cancer, especially in disease evolution and clinical applications, including monitoring tumor progression, diagnosing tumor occurrence, detecting tumor metastasis, and evaluating cancer therapy response. Then, we introduce the latest advances in the combination of MPM with nanomaterials, including the MPM imaging of gold nanoparticles (AuNPs) and carbon dots (CDs). Finally, we also propose the main challenges and future research directions of MPM technology in HCC.

Quantification of multiphoton and fluorescence images of reproductive tissues from a mouse ovarian cancer model shows promise for early disease detection

Ovarian cancer is the deadliest gynecologic cancer due predominantly to late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Multiphoton microscopy (MPM) is a relatively new imaging technique sensitive to endogenous fluorophores, which has tremendous potential for clinical diagnosis, though it is limited in its application to the ovaries. Wide-field fluorescence imaging (WFI) has been proposed as a complementary technique to MPM, as it offers high-resolution imagery of the entire organ and can be tailored to target specific biomarkers that are not captured by MPM imaging. We applied texture analysis to MPM images of a mouse model of ovarian cancer. We also conducted WFI targeting the folate receptor and matrix metalloproteinases. We find that texture analysis of MPM images of the ovary can differentiate between genotypes, which is a proxy for disease, with high statistical significance (p  <  0.001). The wide-field fluorescence signal also changes significantly between genotypes (p  <  0.01). We use the features to classify multiple tissue groups to over 80% accuracy. These results suggest that MPM and WFI are promising techniques for the early detection of ovarian cancer.

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.

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.

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

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

Second harmonic generation microscopy provides accurate automated staging of liver fibrosis in patients with non-alcoholic fatty liver disease

BACKGROUND

Assessment of severity of liver fibrosis is essential in the management of non-alcoholic fatty liver disease (NAFLD). Second Harmonic Generation (SHG) microscopy is a novel optical tissue imaging system that provides automated quantification of fibrosis based on unique architectural features of collagen. This study aims to develop and validate a SHG-based index for automated staging of liver fibrosis in patients with NAFLD.

METHODS

SHG microscopy was performed on archived liver biopsy specimens from 83 patients with NAFLD. A unique algorithm was developed to identify specific SHG parameters that correlated with fibrosis stage. The accuracy of the algorithm was compared against clinical assessment by experienced liver histopathologists using the Brunt fibrosis staging and further validated using the leave-one-out cross-validation method.

RESULTS

Mean age of the study cohort was 51.8 ± 11.7 years, with 41% males. A fibrosis index (SHG B-index) was developed comprising 14 unique SHG-based collagen parameters that correlated with severity of NAFLD fibrosis in a continuous fashion. The SHG B-index had excellent correlation with Brunt fibrosis stage (Spearman's correlation 0.820, p<0.001). AUROCs for prediction of Brunt fibrosis stages 1, 2, 3 and 4 were 0.853, 0.967, 0.985 and 0.941 respectively. In the cross-validation analysis, the SHG B-index demonstrated high specificity for diagnosis of all grades of fibrosis. A SHG B-index score of >1.76 had an overall diagnostic accuracy of 98.5% for prediction of presence of bridging fibrosis (Brunt stage ≥3) with sensitivity of 87.5%, specificity 98.0%, positive predictive value 96.6% and negative predictive value 92.6%.

CONCLUSION

The SHG B-index is a unique SHG-based index that provides accurate automated assessment of fibrosis stage in NAFLD patients.

Platelets' increase is associated with improvement of liver fibrosis in entecavir-treated chronic hepatitis B patients with significant liver fibrosis

BACKGROUND AND AIM

Reduction of platelet count is often observed in chronic hepatitis B (CHB) patients with significant liver fibrosis. In this cohort study, we investigated whether platelets' increase after entecavir (ETV) therapy was associated with the improvement of liver fibrosis.

METHODS

We collected the data of a cohort 82 CHB patients with paired liver biopsies before and after 78-week ETV therapy, and assessed the platelets' change following the treatment and further investigated the associated clinical factors with platelets' change.

RESULTS

Platelet count increased after treatment, which occurred mainly in patients with low baseline level of platelet count (< 200 × 10⁹/L) or with significant fibrosis (Ishak ≥ 3). Regression analysis showed that baseline platelet count was the main factor associated with post-treatment increase of platelets (β = - 0.215, p = 0.015). In patients with significant fibrosis, correlation and linear regression analysis revealed that post-treatment platelets' increase was correlated with improvement of liver fibrosis assessed by reduction of quantitative collagen percentage area (r = 0.392, p = 0.006) (β = 2.449, p = 0.035), but no correlation between changes in platelet counts and Ishak fibrosis score. Receiver operating curve analysis showed an increase of 12.5 × 10⁹/L in platelet count could identify improvement of liver fibrosis (AUC = 0.70).

CONCLUSION

Platelets' increase after ETV therapy was associated to the improvement of liver fibrosis with reduction of collagen percentage area in CHB patients with significant fibrosis.

Quantitative assessment of liver fibrosis (qFibrosis) reveals precise outcomes in Ishak "stable" patients on anti-HBV therapy

Current widely used semiquantitative histological assessment methods are insensitive to identify subtle changes of liver fibrosis. Therefore, to precisely assess therapeutic efficacy on chronic hepatitis B (CHB), we explored the utility of qFibrosis (a fully-quantitative morphometric method employing second harmonic generation/two photon excitation fluorescence) in liver fibrosis evaluation. Fibrosis changes were evaluated by Ishak fibrosis scoring and qFibrosis in CHB patients with paired liver biopsies before and after 78 weeks' antiviral therapy. A total of 162 patients with qualified paired biopsies were enrolled. Ishak fibrosis scoring revealed that 42.6% (69/162) of the patients achieved fibrosis regression (≥1-point decrease), 51.9% (84/162) remained stable, and 5.5% (9/162) showed progression (≥1-point increase). qFibrosis showed similar trends in the groups of regression and progression patients as evaluated by Ishak. However, in Ishak stable patients, qFibrosis revealed hitherto undetected changes, allowing for further subcategorization into regression ("Regression by qFibrosis"; 40/84, 47.6%), stable (29/84, 34.5%), and progression ("Progression by qFibrosis"; 15/84, 17.9%) groups. These newly fine-tuned categories were supported by changes of morphological parameters of fibrosis, collagen percentage area, and liver stiffness measurements. In conclusion, qFibrosis can be used to quantitatively identify subtle changes of liver fibrosis in CHB patients after antiviral therapy.

Changes in serum chitinase 3-like 1 levels correlate with changes in liver fibrosis measured by two established quantitative methods in chronic hepatitis B patients following antiviral therapy

AIM

Non-invasive assessment of changes in liver fibrosis is still an unmet medical need in the era of antiviral therapy. Therefore, we explore whether chitinase 3-like 1 (CHI3L1), a serum marker of liver fibrosis, can be used as a non-invasive surrogate marker of fibrosis change during treatment.

METHODS

We correlated serum CHI3L1 levels with liver tissue collagen proportionate area (CPA) in a cohort of 131 patients with chronic hepatitis B (CHB) receiving entecavir-based antiviral therapy for 78 weeks. In addition, we compared this marker with the liver stiffness measurement (LSM). Multivariate regression analyses were undertaken to determine the clinical factors associated with the CHI3L1 levels.

RESULTS

Before treatment, correlation analysis showed that there were positive correlations between CHI3L1 levels and the CPA (r = 0.351, P < 0.001), and between CHI3L1 and LSM (r = 0.412, P < 0.001). After 78 weeks treatment, serum CHI3L1 levels decreased compared with that at baseline (87.8 vs. 69.6 ng/mL, P < 0.001), and CHI3L1 levels were also correlated with CPA (r = 0.293, P = 0.001) and LSM (r = 0.443, P < 0.001). Furthermore, there were positive correlations between the changes in CHI3L1 and CPA (r = 0.366, P<0.001), and changes in CHI3L1 and LSM (r = 0.438, P<0.001). Multivariate regression analyses indicated that CPA values were related with pre- (β = 5.450, P = 0.019) and post-treatment CHI3L1 levels (β = 7.460, P = 0.023).

CONCLUSIONS

Chitinase 3-like 1 is not only a useful non-invasive marker for the assessment of liver fibrosis in CHB patients before treatment, but also a potential useful marker for monitoring the change in liver fibrosis during therapy.

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.

New classification of liver biopsy assessment for fibrosis in chronic hepatitis B patients before and after treatment

Liver fibrosis is the net result of dynamic changes between fibrogenesis and fibrolysis. Evidence has shown that antiviral therapy can reverse liver fibrosis or even early cirrhosis caused by hepatitis B virus. However, current evaluation systems mainly focus on the severity of, but not the dynamic changes in, fibrosis. Here, we propose a new classification to evaluate the dynamic changes in the quality of fibrosis, namely: predominantly progressive (thick/broad/loose/pale septa with inflammation); predominately regressive (delicate/thin/dense/splitting septa); and indeterminate, which displayed an overall balance between progressive and regressive scarring. Then, we used this classification to evaluate 71 paired liver biopsies of chronic hepatitis B patients before and after entecavir-based therapy for 78 weeks. Progressive, indeterminate, and regressive were observed in 58%, 29%, and 13% of patients before treatment versus in 11%, 11%, and 78% after treatment. Of the 55 patients who showed predominantly regressive changes on posttreatment liver biopsy, 29 cases (53%) had fibrosis improvement of at least one Ishak stage, and, more interestingly, 25 cases (45%) had significant improvement in terms of Laennec substage, collagen percentage area, and liver stiffness despite remaining in the same Ishak stage.

CONCLUSION

This new classification highlights the importance of assessing and identifying the dynamic changes in the quality of fibrosis, especially relevant in the era of antiviral therapy.(Hepatology 2017;65:1438-1450).

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

Animal models provide a useful platform for developing and testing new drugs to treat liver fibrosis. Accordingly, we developed a novel automated system to evaluate liver fibrosis in rodent models. This system uses second-harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy to assess a total of four mouse and rat models, using chemical treatment with either thioacetamide (TAA) or carbon tetrachloride (CCl₄), and a surgical method, bile duct ligation (BDL). The results obtained by the new technique were compared with that using Ishak fibrosis scores and two currently used quantitative methods for determining liver fibrosis: the collagen proportionate area (CPA) and measurement of hydroxyproline (HYP) content. We show that 11 shared morphological parameters faithfully recapitulate Ishak fibrosis scores in the models, with high area under the receiver operating characteristic (ROC) curve (AUC) performance. The AUC values of 11 shared parameters were greater than that of the CPA (TAA: 0.758-0.922 vs 0.752-0.908; BDL: 0.874-0.989 vs 0.678-0.966) in the TAA mice and BDL rat models and similar to that of the CPA in the TAA rat and CCl₄ mouse models. Similarly, based on the trends in these parameters at different time points, 9, 10, 7, and 2 model-specific parameters were selected for the TAA rats, TAA mice, CCl₄ mice, and BDL rats, respectively. These parameters identified differences among the time points in the four models, with high AUC accuracy, and the corresponding AUC values of these parameters were greater compared with those of the CPA in the TAA rat and mouse models (rats: 0.769-0.894 vs 0.64-0.799; mice: 0.87-0.93 vs 0.739-0.836) and similar to those of the CPA in the CCl₄ mouse and BDL rat models. Similarly, the AUC values of 11 shared parameters and model-specific parameters were greater than those of HYP in the TAA rats, TAA mice, and CCl₄ mouse models and were similar to those of HYP in the BDL rat models. The automated evaluation system, combined with 11 shared parameters and model-specific parameters, could specifically, accurately, and quantitatively stage liver fibrosis in animal models.

Visualizing liver anatomy, physiology and pharmacology using multiphoton microscopy

Multiphoton microscopy (MPM) has become increasingly popular and widely used in both basic and clinical liver studies over the past few years. This technology provides insights into deep live tissues with less photobleaching and phototoxicity, which helps us to better understand the cellular morphology, microenvironment, immune responses and spatiotemporal dynamics of drugs and therapeutic cells in the healthy and diseased liver. This review summarizes the principles, opportunities, applications and limitations of MPM in hepatology. A key emphasis is on the use of fluorescence lifetime imaging (FLIM) to add additional quantification and specificity to the detection of endogenous fluorescent species in the liver as well as exogenous molecules and nanoparticles that are applied to the liver in vivo. We anticipate that in the near future MPM-FLIM will advance our understanding of the cellular and molecular mechanisms of liver diseases, and will be evaluated from bench to bedside, leading to real-time histology of human liver diseases.

Efficient second-harmonic imaging of collagen in histological slides using Bessel beam excitation

Second-harmonic generation (SHG) is the most specific label-free indicator of collagen accumulation in widespread pathologies such as fibrosis, and SHG-based measurements hold important potential for biomedical analyses. However, efficient collagen SHG scoring in histological slides is hampered by the limited depth-of-field of usual nonlinear microscopes relying on focused Gaussian beam excitation. In this work we analyze theoretically and experimentally the use of Bessel beam excitation to address this issue. Focused Bessel beams can provide an axially extended excitation volume for nonlinear microscopy while preserving lateral resolution. We show that shaping the focal volume has consequences on signal level and scattering directionality in the case of coherent signals (such as SHG) which significantly differ from the case of incoherent signals (two-photon excited fluorescence, 2PEF). We demonstrate extended-depth SHG-2PEF imaging of fibrotic mouse kidney histological slides. Finally, we show that Bessel beam excitation combined with spatial filtering of the harmonic light in wave vector space can be used to probe collagen accumulation more efficiently than the usual Gaussian excitation scheme. These results open the way to SHG-based histological diagnoses.

Quantification of liver fibrosis via second harmonic imaging of the Glisson's capsule from liver surface

Liver surface is covered by a collagenous layer called the Glisson's capsule. The structure of the Glisson's capsule is barely seen in the biopsy samples for histology assessment, thus the changes of the collagen network from the Glisson's capsule during the liver disease progression are not well studied. In this report, we investigated whether non-linear optical imaging of the Glisson's capsule at liver surface would yield sufficient information to allow quantitative staging of liver fibrosis. In contrast to conventional tissue sections whereby tissues are cut perpendicular to the liver surface and interior information from the liver biopsy samples were used, we have established a capsule index based on significant parameters extracted from the second harmonic generation (SHG) microscopy images of capsule collagen from anterior surface of rat livers. Thioacetamide (TAA) induced liver fibrosis animal models was used in this study. The capsule index is capable of differentiating different fibrosis stages, with area under receiver operating characteristics curve (AUC) up to 0.91, making it possible to quantitatively stage liver fibrosis via liver surface imaging potentially with endomicroscopy.

Differential remodeling of extracellular matrices by breast cancer initiating cells

Cancer initiating cells (CICs) have been the focus of recent anti-cancer therapies, exhibiting strong invasion capability via potentially enhanced ability to remodel extracellular matrices (ECM). We have identified CICs in a human breast cancer cell line, MX-1, and developed a xenograft model in SCID mice. We investigated the CICs' matrix-remodeling effects using Second Harmonic Generation (SHG) microscopy to identify potential phenotypic signatures of the CIC-rich tumors. The isolated CICs exhibit higher proliferation, drug efflux and drug resistant properties in vitro; were more tumorigenic than non-CICs, resulting in more and larger tumors in the xenograft model. The CIC-rich tumors have less collagen in the tumor interior than in the CIC-poor tumors supporting the idea that the CICs can remodel the collagen more effectively. The collagen fibers were preferentially aligned perpendicular to the CIC-rich tumor boundary while parallel to the CIC-poor tumor boundary suggesting more invasive behavior of the CIC-rich tumors. These findings would provide potential translational values in quantifying and monitoring CIC-rich tumors in future anti-cancer therapies. CIC-rich tumors remodel the collagen matrix more than CIC-poor tumors.

Current strategies for quantitating fibrosis in liver biopsy

Objective:

The present mini-review updated the progress in methodologies based on using liver biopsy.

Data Sources:

Articles for study of liver fibrosis, liver biopsy or fibrosis assessment published on high impact peer review journals from 1980 to 2014.

Study Selection:

Key articles were selected mainly according to their levels of relevance to this topic and citations.

Results:

With the recently mounting progress in chronic liver disease therapeutics, comes by a pressing need for precise, accurate, and dynamic assessment of hepatic fibrosis and cirrhosis in individual patients. Histopathological information is recognized as the most valuable data for fibrosis assessment. Conventional histology categorical systems describe the changes of fibrosis patterns in liver tissue; but the simplified ordinal digits assigned by these systems cannot reflect the fibrosis dynamics with sufficient precision and reproducibility. Morphometric assessment by computer assist digital image analysis, such as collagen proportionate area (CPA), detects change of fibrosis amount in tissue section in a continuous variable, and has shown its independent diagnostic value for assessment of advanced or late-stage of fibrosis. Due to its evident sensitivity to sampling variances, morphometric measurement is feasible to be taken as a reliable statistical parameter for the study of a large cohort. Combining state-of-art imaging technology and fundamental principle in Tissue Engineering, structure-based quantitation was recently initiated with a novel proof-of-concept tool, qFibrosis. qFibrosis showed not only the superior performance to CPA in accurately and reproducibly differentiating adjacent stages of fibrosis, but also the possibility for facilitating analysis of fibrotic regression and cirrhosis sub-staging.

Conclusions:

With input from multidisciplinary innovation, liver biopsy assessment as a new “gold standard” is anticipated to substantially support the accelerated progress of Hepatology medicine.

Automated biphasic morphological assessment of hepatitis B-related liver fibrosis using second harmonic generation microscopy

Liver fibrosis assessment by biopsy and conventional staining scores is based on histopathological criteria. Variations in sample preparation and the use of semi-quantitative histopathological methods commonly result in discrepancies between medical centers. Thus, minor changes in liver fibrosis might be overlooked in multi-center clinical trials, leading to statistically non-significant data. Here, we developed a computer-assisted, fully automated, staining-free method for hepatitis B-related liver fibrosis assessment. In total, 175 liver biopsies were divided into training (n = 105) and verification (n = 70) cohorts. Collagen was observed using second harmonic generation (SHG) microscopy without prior staining, and hepatocyte morphology was recorded using two-photon excitation fluorescence (TPEF) microscopy. The training cohort was utilized to establish a quantification algorithm. Eleven of 19 computer-recognizable SHG/TPEF microscopic morphological features were significantly correlated with the ISHAK fibrosis stages (P < 0.001). A biphasic scoring method was applied, combining support vector machine and multivariate generalized linear models to assess the early and late stages of fibrosis, respectively, based on these parameters. The verification cohort was used to verify the scoring method, and the area under the receiver operating characteristic curve was >0.82 for liver cirrhosis detection. Since no subjective gradings are needed, interobserver discrepancies could be avoided using this fully automated method.

Phase and Texture Characterizations of Scar Collagen Second-Harmonic Generation Images Varied with Scar Duration

This work developed a phase congruency algorithm combined with texture analysis to quantitatively characterize collagen morphology in second-harmonic generation (SHG) images from human scars. The extracted phase and texture parameters of the SHG images quantified collagen directionality, homogeneity, and coarseness in scars and varied with scar duration. Phase parameters showed an increasing tendency of the mean of phase congruency with scar duration, indicating that collagen fibers are better oriented over time. Texture parameters calculated from local difference local binary pattern (LD-LBP) and Haar wavelet transform, demonstrated that the LD-LBP variance decreased and the energy of all subimages increased with scar duration. It implied that collagen has a more regular pattern and becomes coarser with scar duration. In addition, the random forest regression was used to predict scar duration, demonstrating reliable performance of the extracted phase and texture parameters in characterizing collagen morphology in scar SHG images. Results indicate that the extracted parameters using the proposed method can be used as quantitative indicators to monitor scar progression with time and can help understand the mechanism of scar progression.

Evaluation of area-based collagen scoring by nonlinear microscopy in chronic hepatitis C-induced liver fibrosis

In this paper we analyze a fibrosis scoring method based on measurement of the fibrillar collagen area from second harmonic generation (SHG) microscopy images of unstained histological slices from human liver biopsies. The study is conducted on a cohort of one hundred chronic hepatitis C patients with intermediate to strong Metavir and Ishak stages of liver fibrosis. We highlight a key parameter of our scoring method to discriminate between high and low fibrosis stages. Moreover, according to the intensity histograms of the SHG images and simple mathematical arguments, we show that our area-based method is equivalent to an intensity-based method, despite saturation of the images. Finally we propose an improvement of our scoring method using very simple image processing tools.

Improving femtosecond laser pulse delivery through a hollow core photonic crystal fiber for temporally focused two-photon endomicroscopy

In this paper, we present a strategy to improve delivery of femtosecond laser pulses from a regenerative amplifier through a hollow core photonic crystal fiber for temporally focused wide-field two-photon endomicroscopy. For endomicroscope application, wide-field two-photon excitation has the advantage of requiring no scanning in the distal end. However, wide-field two-photon excitation requires peak power that is 10(4)-10(5) times higher than the point scanning approach corresponding to femtosecond pulses with energy on the order of 1-10 μJ at the specimen plane. The transmission of these high energy pulses through a single mode fiber into the microendoscope is a significant challenge. Two approaches were pursued to partially overcome this limitation. First, a single high energy pulse is split into a train of pulses with energy below the fiber damage threshold better utilizing the available laser energy. Second, stretching the pulse width in time by introducing negative dispersion was shown to have the dual benefit of reducing fiber damage probability and compensating for the positive group velocity dispersion induced by the fiber. With these strategy applied, 11 fold increase in the two photon excitation signal has been demonstrated.

Texture analysis applied to second harmonic generation image data for ovarian cancer classification

Remodeling of the extracellular matrix has been implicated in ovarian cancer. To quantitate the remodeling, we implement a form of texture analysis to delineate the collagen fibrillar morphology observed in second harmonic generation microscopy images of human normal and high grade malignant ovarian tissues. In the learning stage, a dictionary of “textons”—frequently occurring texture features that are identified by measuring the image response to a filter bank of various shapes, sizes, and orientations—is created. By calculating a representative model based on the texton distribution for each tissue type using a training set of respective second harmonic generation images, we then perform classification between images of normal and high grade malignant ovarian tissues. By optimizing the number of textons and nearest neighbors, we achieved classification accuracy up to 97% based on the area under receiver operating characteristic curves (true positives versus false positives). The local analysis algorithm is a more general method to probe rapidly changing fibrillar morphologies than global analyses such as FFT. It is also more versatile than other texture approaches as the filter bank can be highly tailored to specific applications (e.g., different disease states) by creating customized libraries based on common image features.

High-throughput nonlinear optical microscopy

High-resolution microscopy methods based on different nonlinear optical (NLO) contrast mechanisms are finding numerous applications in biology and medicine. While the basic implementations of these microscopy methods are relatively mature, an important direction of continuing technological innovation lies in improving the throughput of these systems. Throughput improvement is expected to be important for studying fast kinetic processes, for enabling clinical diagnosis and treatment, and for extending the field of image informatics. This review will provide an overview of the fundamental limitations on NLO microscopy throughput. We will further cover several important classes of high-throughput NLO microscope designs with discussions on their strengths and weaknesses and their key biomedical applications. Finally, this review will close with a perspective of potential future technological improvements in this field.

qFibrosis: a fully-quantitative innovative method incorporating histological features to facilitate accurate fibrosis scoring in animal model and chronic hepatitis B patients

BACKGROUND & AIMS

There is increasing need for accurate assessment of liver fibrosis/cirrhosis. We aimed to develop qFibrosis, a fully-automated assessment method combining quantification of histopathological architectural features, to address unmet needs in core biopsy evaluation of fibrosis in chronic hepatitis B (CHB) patients.

METHODS

qFibrosis was established as a combined index based on 87 parameters of architectural features. Images acquired from 25 Thioacetamide-treated rat samples and 162 CHB core biopsies were used to train and test qFibrosis and to demonstrate its reproducibility. qFibrosis scoring was analyzed employing Metavir and Ishak fibrosis staging as standard references, and collagen proportionate area (CPA) measurement for comparison.

RESULTS

qFibrosis faithfully and reliably recapitulates Metavir fibrosis scores, as it can identify differences between all stages in both animal samples (p<0.001) and human biopsies (p<0.05). It is robust to sampling size, allowing for discrimination of different stages in samples of different sizes (area under the curve (AUC): 0.93-0.99 for animal samples: 1-16 mm(2); AUC: 0.84-0.97 for biopsies: 10-44 mm in length). qFibrosis can significantly predict staging underestimation in suboptimal biopsies (<15 mm) and under- and over-scoring by different pathologists (p<0.001). qFibrosis can also differentiate between Ishak stages 5 and 6 (AUC: 0.73, p=0.008), suggesting the possibility of monitoring intra-stage cirrhosis changes. Best of all, qFibrosis demonstrates superior performance to CPA on all counts.

CONCLUSIONS

qFibrosis can improve fibrosis scoring accuracy and throughput, thus allowing for reproducible and reliable analysis of efficacies of anti-fibrotic therapies in clinical research and practice.

Experimenting liver fibrosis diagnostic by two photon excitation microscopy and Bag-of-Features image classification

The accurate staging of liver fibrosis is of paramount importance to determine the state of disease progression, therapy responses, and to optimize disease treatment strategies. Non-linear optical microscopy techniques such as two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) can image the endogenous signals of tissue structures and can be used for fibrosis assessment on non-stained tissue samples. While image analysis of collagen in SHG images was consistently addressed until now, cellular and tissue information included in TPEF images, such as inflammatory and hepatic cell damage, equally important as collagen deposition imaged by SHG, remain poorly exploited to date. We address this situation by experimenting liver fibrosis quantification and scoring using a combined approach based on TPEF liver surface imaging on a Thioacetamide-induced rat model and a gradient based Bag-of-Features (BoF) image classification strategy. We report the assessed performance results and discuss the influence of specific BoF parameters to the performance of the fibrosis scoring framework.

Single vs. two-photon microscopy for label free intrinsic tissue studies in the UV light region

Single photon ultraviolet microscopy is complementary to two-photon microscopy for tissue diagnosis.