Hepatic steatosis estimated microscopically versus digital image analysis

Steatotic Donor Transplant Livers: Preservation Strategies to Mitigate against Ischaemia-Reperfusion Injury

Liver transplantation (LT) is the only definitive treatment for end-stage liver disease, yet the UK has seen a 400% increase in liver disease-related deaths since 1970, constrained further by a critical shortage of donor organs. This shortfall has necessitated the use of extended criteria donor organs, including those with evidence of steatosis. The impact of hepatic steatosis (HS) on graft viability remains a concern, particularly for donor livers with moderate to severe steatosis which are highly sensitive to the process of ischaemia-reperfusion injury (IRI) and static cold storage (SCS) leading to poor post-transplantation outcomes. This review explores the pathophysiological predisposition of steatotic livers to IRI, the limitations of SCS, and alternative preservation strategies, including novel organ preservation solutions (OPS) and normothermic machine perfusion (NMP), to mitigate IRI and improve outcomes for steatotic donor livers. By addressing these challenges, the liver transplant community can enhance the utilisation of steatotic donor livers which is crucial in the context of the global obesity crisis and the growing need to expand the donor pool.

[Challenges of automation in quantitative evaluation of liver biopsies : Automatic quantification of liver steatosis]

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD), or non-alcoholic fatty liver disease (NAFLD), is a common disease that is diagnosed through manual evaluation of liver biopsies, an assessment that is subject to high interobserver variability (IBV). IBV can be reduced using automated methods.

OBJECTIVES

Many existing computer-based methods do not accurately reflect what pathologists evaluate in practice. The goal is to demonstrate how these differences impact the prediction of hepatic steatosis. Additionally, IBV complicates algorithm validation.

MATERIALS AND METHODS

Forty tissue sections were analyzed to detect steatosis, nuclei, and fibrosis. Data generated from automated image processing were used to predict steatosis grades. To investigate IBV, 18 liver biopsies were evaluated by multiple observers.

RESULTS

Area-based approaches yielded more strongly correlated results than nucleus-based methods (⌀ Spearman rho [ρ] = 0.92 vs. 0.79). The inclusion of information regarding tissue composition reduced the average absolute error for both area- and nucleus-based predictions by 0.5% and 2.2%, respectively. Our final area-based algorithm, incorporating tissue structure information, achieved a high accuracy (80%) and strong correlation (⌀ Spearman ρ = 0.94) with manual evaluation.

CONCLUSION

The automatic and deterministic evaluation of steatosis can be improved by integrating information about tissue composition and can serve to reduce the influence of IBV.

Assessment of large droplet fat in frozen sections of donor liver biopsies: utility and interobserver variability of the newly described Banff method compared to a simplified Average of Fields method

AIMS

There is great variability in the assessment and reporting of fat in frozen sections of donor liver biopsies. The Banff Working Group has proposed a novel method and definition for scoring large droplet fat (LDF) in donor liver biopsies. This study compares the Banff method with a simpler Average of Fields (AF) method and evaluates the impact of different LDF definitions.

METHODS

Three pathologists assessed percentage of LDF (LDF%) in 10 donor liver biopsies using Banff and AF methods, applying the Banff LDF definition (cell distention with a single droplet larger than adjacent hepatocytes). Additionally, LDF% by the AF method was compared using two LDF definitions: Banff definition versus LDF definition 2 (single fat droplet occupying greater than half of a hepatocyte with nuclear displacement).

RESULTS

Intraobserver concordance between the Banff and AF methods was similar for all three pathologists (kappa 0.76-1). Both methods exhibited 70% interobserver concordance, and there was substantial agreement (kappa 0.68) in the LDF% among the three pathologists for both methods. Comparing the two LDF definitions, results were significantly lower with the Banff definition; LDF >50% was observed in four cases with LDF definition 2 but none of the cases with the Banff definition.

CONCLUSIONS

There is high interobserver and intraobserver concordance of LDF% between the Banff and AF methods. LDF% determined by the Banff definition was lower than with LDF definition 2, and needs to be validated based on graft outcome before it can be recommended for clinical use.

Comparing magnetic resonance liver fat fraction measurements with histology in fibrosis: the difference between proton density fat fraction and tissue mass fat fraction

OBJECTIVE

Magnetic resonance spectroscopy (MRS) provides a powerful method of measuring fat fraction. However, previous studies have shown that MRS results give lower values compared with visual estimates from biopsies in fibrotic livers. This study investigated these discrepancies and considered whether a tissue water content correction, as assessed by MRI relaxometry, could provide better agreement.

MATERIALS AND METHODS

110 patients were scanned in a 1.5 T Philips scanner and biopsies were obtained. Multiple echo MRS (30 × 30 ×  30 mm volume) was used to determine Proton Density Fat Fraction (PDFF). Biopsies were assessed by visual assessment for fibrosis and steatosis grading. Digital image analysis (DIA) was also used to quantify fat fraction within tissue samples. T1 relaxation times were then used to estimate tissue water content to correct PDFF for confounding factors.

RESULTS

PDFF values across the four visually assessed steatosis grades were significantly less in the higher fibrosis group (F3-F4) compared to the lower fibrosis group (F0-F2). The slope of the linear regression of PDFF vs DIA fat fraction was ~ 1 in the low fibrosis group and 0.77 in the high fibrosis group. Correcting for water content based on T1 increased the gradient but it did not reach unity.

DISCUSSION

In fibrotic livers, PDFF underestimated fat fraction compared to DIA methods. Values were improved by applying a water content correction, but fat fractions were still underestimated.

Development of a portable device to quantify hepatic steatosis in potential donor livers

An accurate estimation of liver fat content is necessary to predict how a donated liver will function after transplantation. Currently, a pathologist needs to be available at all hours of the day, even at remote hospitals, when an organ donor is procured. Even among expert pathologists, the estimation of liver fat content is operator-dependent. Here we describe the development of a low-cost, end-to-end artificial intelligence platform to evaluate liver fat content on a donor liver biopsy slide in real-time. The hardware includes a high-resolution camera, display, and GPU to acquire and process donor liver biopsy slides. A deep learning model was trained to label and quantify fat globules in liver tissue. The algorithm was deployed on the device to enable real-time quantification and characterization of fat content for transplant decision-making. This information is displayed on the device and can also be sent to a cloud platform for further analysis.

How to Preserve Steatotic Liver Grafts for Transplantation

Liver allograft steatosis is a significant risk factor for postoperative graft dysfunction and has been associated with inferior patient and graft survival, particularly in the case of moderate or severe macrovesicular steatosis. In recent years, the increasing incidence of obesity and fatty liver disease in the population has led to a higher proportion of steatotic liver grafts being used for transplantation, making the optimization of their preservation an urgent necessity. This review discusses the mechanisms behind the increased susceptibility of fatty livers to ischemia-reperfusion injury and provides an overview of the available strategies to improve their utilization for transplantation, with a focus on preclinical and clinical evidence supporting donor interventions, novel preservation solutions, and machine perfusion techniques.

Automated Segmentation and Morphological Characterization of Hepatic Steatosis and Correlation with Histopathology

BACKGROUND/OBJECTIVES

Prevalence of nonalcoholic fatty liver disease (NAFLD) has increased to 25% of the world population. Hepatic steatosis is a hallmark feature of NAFLD and is assessed histologically using visual and ordinal fat grading criteria (0-3) from the Nonalcoholic Steatohepatitis (NASH) Clinical Research Network (CRN) scoring system. The purpose of this study is to automatically segment and extract morphological characteristics and distributions of fat droplets (FDs) on liver histology images and find associations with severity of steatosis.

METHODS

A previously published human cohort of 68 NASH candidates was graded for steatosis by an experienced pathologist using the Fat CRN grading system. The automated segmentation algorithm quantified fat fraction (FF) and fat-affected hepatocyte ratio (FHR), extracted fat morphology by calculating radius and circularity of FDs, and examined FDs distribution and heterogeneity using nearest neighbor distance and regional isotropy.

RESULTS

Regression analysis and Spearman correlation (ρ) yielded high correlations for radius (R2 = 0.86, ρ = 0.72), nearest neighbor distance (R2 = 0.82, ρ = -0.82), regional isotropy (R2 = 0.84, ρ = 0.74), and FHR (R2 = 0.90, ρ = 0.85), and low correlation for circularity (R2 = 0.48, ρ = -0.32) with FF and pathologist grades, respectively. FHR showed a better distinction between pathologist Fat CRN grades compared to conventional FF measurements, making it a potential surrogate measure for Fat CRN scores. Our results showed variation in distribution of morphological features and steatosis heterogeneity within the same patient's biopsy sample as well as between patients of similar FF.

CONCLUSIONS

The fat percentage measurements, specific morphological characteristics, and patterns of distribution quantified with the automated segmentation algorithm showed associations with steatosis severity; however, future studies are warranted to evaluate the clinical significance of these steatosis features in progression of NAFLD and NASH.

Digital imaging software versus the "eyeball" method in quantifying steatosis in a liver biopsy

Steatotic livers represent a potentially underutilized resource to increase the donor graft pool; however, 1 barrier to the increased utilization of such grafts is the heterogeneity in the definition and the measurement of macrovesicular steatosis (MaS). Digital imaging software (DIS) may better standardize definitions to study posttransplant outcomes. Using HALO, a DIS, we analyzed 63 liver biopsies, from 3 transplant centers, transplanted between 2016 and 2018, and compared macrovesicular steatosis percentage (%MaS) as estimated by transplant center, donor hospital, and DIS. We also quantified the relationship between DIS characteristics and posttransplant outcomes using log-linear regression for peak aspartate aminotransferase, peak alanine aminotransferase, and total bilirubin on postoperative day 7, as well as logistic regression for early allograft dysfunction. Transplant centers and donor hospitals overestimated %MaS compared with DIS, with better agreement at lower %MaS and less agreement for higher %MaS. No DIS analyzed liver biopsies were calculated to be >20% %MaS; however, 40% of liver biopsies read by transplant center pathologists were read to be >30%. Percent MaS read by HALO was positively associated with peak aspartate aminotransferase (regression coefficient= 1.04 1.08 1.12 , p <0.001), peak alanine aminotransferase (regression coefficient = 1.04 1.08 1.12 , p <0.001), and early allograft dysfunction (OR= 1.10 1.40 1.78 , p =0.006). There was no association between HALO %MaS and total bilirubin on postoperative day 7 (regression coefficient = 0.99 1.01 1.04 , p =0.3). DIS provides reproducible quantification of steatosis that could standardize MaS definitions and identify phenotypes associated with good clinical outcomes to increase the utilization of steatite livers.

Artificial intelligence for prediction of donor liver allograft steatosis and early post-transplantation graft failure

BACKGROUND

Donor livers undergo subjective pathologist review of steatosis before transplantation to mitigate the risk for early allograft dysfunction (EAD). We developed an objective, computer vision artificial intelligence (CVAI) platform to score donor liver steatosis and compared its capability for predicting EAD against pathologist steatosis scores.

METHODS

Two pathologists scored digitized donor liver biopsy slides from 2014 to 2019. We trained four CVAI platforms with 1:99 training:prediction split. Mean intersection-over-union (IU) characterized CVAI model accuracy. We defined EAD using liver function tests within 1 week of transplantation. We calculated separate EAD logistic regression models with CVAI and pathologist steatosis and compared the models' discrimination and internal calibration.

RESULTS

From 90 liver biopsies, 25,494 images trained CVAI models yielding peak mean IU = 0.80. CVAI steatosis scores were lower than pathologist scores (median 3% vs 20%, P < 0.001). Among 41 transplanted grafts, 46% developed EAD. The median CVAI steatosis score was higher for those with EAD (2.9% vs 1.9%, P = 0.02). CVAI steatosis was independently associated with EAD after adjusting for donor age, donor diabetes, and MELD score (aOR = 1.34, 95%CI = 1.03-1.75, P = 0.03).

CONCLUSION

The CVAI steatosis EAD model demonstrated slightly better calibration than pathologist steatosis, meriting further investigation into which modality most accurately and reliably predicts post-transplantation outcomes.

Mitochondrial respiratory chain and Krebs cycle enzyme function in human donor livers subjected to end-ischaemic hypothermic machine perfusion

INTRODUCTION

Marginal human donor livers are highly susceptible to ischaemia reperfusion injury and mitochondrial dysfunction. Oxygenation during hypothermic machine perfusion (HMP) was proposed to protect the mitochondria but the mechanism is unclear. Additionally, the distribution and uptake of perfusate oxygen during HMP are unknown. This study aimed to examine the feasibility of mitochondrial function analysis during end-ischaemic HMP, assess potential mitochondrial viability biomarkers, and record oxygenation kinetics.

METHODS

This was a randomised pilot study using human livers retrieved for transplant but not utilised. Livers (n = 38) were randomised at stage 1 into static cold storage (n = 6), hepatic artery HMP (n = 7), and non-oxygen supplemented portal vein HMP (n = 7) and at stage 2 into oxygen supplemented and non-oxygen supplemented portal vein HMP (n = 11 and 7, respectively). Mitochondrial parameters were compared between the groups and between low- and high-risk marginal livers based on donor history, organ steatosis and preservation period. The oxygen delivery efficiency was assessed in additional 6 livers using real-time measurements of perfusate and parenchymal oxygen.

RESULTS

The change in mitochondrial respiratory chain (complex I, II, III, IV) and Krebs cycle enzyme activity (aconitase, citrate synthase) before and after 4-hour preservation was not different between groups in both study stages (p > 0.05). Low-risk livers that could have been used clinically (n = 8) had lower complex II-III activities after 4-hour perfusion, compared with high-risk livers (73 nmol/mg/min vs. 113 nmol/mg/min, p = 0.01). Parenchymal pO2 was consistently lower than perfusate pO2 (p ≤ 0.001), stabilised in 28 minutes compared to 3 minutes in perfusate (p = 0.003), and decreased faster upon oxygen cessation (75 vs. 36 minutes, p = 0.003).

CONCLUSIONS

Actively oxygenated and air-equilibrated end-ischaemic HMP did not induce oxidative damage of aconitase, and respiratory chain complexes remained intact. Mitochondria likely respond to variable perfusate oxygen levels by adapting their respiratory function during end-ischaemic HMP. Complex II-III activities should be further investigated as viability biomarkers.

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.

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

BACKGROUND

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

AIMS

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

RESULTS

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

CONCLUSION

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

High-Throughput, Machine Learning-Based Quantification of Steatosis, Inflammation, Ballooning, and Fibrosis in Biopsies From Patients With Nonalcoholic Fatty Liver Disease

BACKGROUND & AIMS

Liver biopsy is the reference standard for staging and grading nonalcoholic fatty liver disease (NAFLD), but histologic scoring systems are semiquantitative with marked interobserver and intraobserver variation. We used machine learning to develop fully automated software for quantification of steatosis, inflammation, ballooning, and fibrosis in biopsy specimens from patients with NAFLD and validated the technology in a separate group of patients.

METHODS

We collected data from 246 consecutive patients with biopsy-proven NAFLD and followed up in London from January 2010 through December 2016. Biopsy specimens from the first 100 patients were used to derive the algorithm and biopsy specimens from the following 146 were used to validate it. Biopsy specimens were scored independently by pathologists using the Nonalcoholic Steatohepatitis Clinical Research Network criteria and digitalized. Areas of steatosis, inflammation, ballooning, and fibrosis were annotated on biopsy specimens by 2 hepatobiliary histopathologists to facilitate machine learning. Images of biopsies from the derivation and validation sets then were analyzed by the algorithm to compute percentages of fat, inflammation, ballooning, and fibrosis, as well as the collagen proportionate area, and compared with findings from pathologists' manual annotations and conventional scoring systems.

RESULTS

In the derivation group, results from manual annotation and the software had an interclass correlation coefficient (ICC) of 0.97 for steatosis (95% CI, 0.95-0.99; P < .001); ICC of 0.96 for inflammation (95% CI, 0.9-0.98; P < .001); ICC of 0.94 for ballooning (95% CI, 0.87-0.98; P < .001); and ICC of 0.92 for fibrosis (95% CI, 0.88-0.96; P = .001). Percentages of fat, inflammation, ballooning, and the collagen proportionate area from the derivation group were confirmed in the validation cohort. The software identified histologic features of NAFLD with levels of interobserver and intraobserver agreement ranging from 0.95 to 0.99; this value was higher than that of semiquantitative scoring systems, which ranged from 0.58 to 0.88. In a subgroup of paired liver biopsy specimens, quantitative analysis was more sensitive in detecting differences compared with the nonalcoholic steatohepatitis Clinical Research Network scoring system.

CONCLUSIONS

We used machine learning to develop software to rapidly and objectively analyze liver biopsy specimens for histologic features of NAFLD. The results from the software correlate with those from histopathologists, with high levels of interobserver and intraobserver agreement. Findings were validated in a separate group of patients. This tool might be used for objective assessment of response to therapy for NAFLD in practice and clinical trials.

Enhancing the Value of Histopathological Assessment of Allograft Biopsy Monitoring

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

Fully automated quantitative assessment of hepatic steatosis in liver transplants

BACKGROUND

The presence of macro- and microvesicular steatosis is one of the major risk factors for liver transplantation. An accurate assessment of the steatosis percentage is crucial for determining liver graft transplantability, which is currently based on the pathologists' visual evaluations on liver histology specimens.

METHOD

The aim of this study was to develop and validate a fully automated algorithm, called HEPASS (HEPatic Adaptive Steatosis Segmentation), for both micro- and macro-steatosis detection in digital liver histological images. The proposed method employs a hybrid deep learning framework, combining the accuracy of an adaptive threshold with the semantic segmentation of a deep convolutional neural network. Starting from all white regions, the HEPASS algorithm was able to detect lipid droplets and classify them into micro- or macrosteatosis.

RESULTS

The proposed method was developed and tested on 385 hematoxylin and eosin (H&E) stained images coming from 77 liver donors. Automated results were compared with manual annotations and nine state-of-the-art techniques designed for steatosis segmentation. In the TEST set, the algorithm was characterized by 97.27% accuracy in steatosis quantification (average error 1.07%, maximum average error 5.62%) and outperformed all the compared methods.

CONCLUSIONS

To the best of our knowledge, the proposed algorithm is the first fully automated algorithm for the assessment of both micro- and macrosteatosis in H&E stained liver tissue images. Being very fast (average computational time 0.72 s), this algorithm paves the way for automated, quantitative and real-time liver graft assessments.

Acute Kidney Injury Patterns Following Transplantation of Steatotic Liver Allografts

BACKGROUND

Steatotic grafts are increasingly being used for liver transplant (LT); however, the impact of graft steatosis on renal function has not been well described.

METHODS

A total of 511 allografts from Mayo Clinic Arizona and Minnesota were assessed. We evaluated post-LT acute kidney injury (AKI) patterns, perioperative variables and one-year outcomes for patients receiving moderately steatotic allografts (>30% macrovesicular steatosis, n = 40) and compared them to non-steatotic graft recipients.

RESULTS

Post-LT AKI occurred in 52.5% of steatotic graft recipients versus 16.7% in non-steatotic recipients (p < 0.001). Ten percent of steatotic graft recipients required new dialysis post-LT (p = 0.003). At five years, there were no differences for AKI vs. no AKI patient survival (HR 0.95, 95% CI 0.08-10.6, p = 0.95) or allograft survival (HR 1.73, 95% CI 0.23-13.23, p = 0.59) for those using steatotic grafts. Lipopeliosis on biopsy was common in those who developed AKI (61.0% vs. 31.6%, p = 0.04), particularly when the Model for End-Stage Liver Disease (MELD) was ≥20 (88.9%; p = 0.04). Lipopeliosis was a predictor of post-LT AKI (OR 6.0, 95% CI 1.1-34.6, p = 0.04).

CONCLUSION

One-year outcomes for moderately steatotic grafts are satisfactory; however, a higher percentage of post-LT AKI and initiation of dialysis can be expected. Presence of lipopeliosis on biopsy appears to be predictive of post-LT AKI.

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

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

A Novel Automatic Digital Algorithm that Accurately Quantifies Steatosis in NAFLD on Histopathological Whole-Slide Images

Background

Accurate assessment of hepatic steatosis is a key to grade disease severity in non‐alcoholic fatty liver disease (NAFLD).

Methods

We developed a digital automated quantification of steatosis on whole‐slide images (WSIs) of liver tissue and performed a validation study. Hematoxylin–eosin stained liver tissue slides were digitally scanned, and steatotic areas were manually annotated. We identified thresholds for size and roundness parameters by logistic regression to discriminate steatosis from surrounding liver tissue. The resulting algorithm produces a steatosis proportionate area (SPA; ratio of steatotic area to total tissue area described as percentage). The software can be implemented as a Java plug‐in in FIJI, in which digital WSI can be processed automatically using the Pathomation extension.

Results

We obtained liver tissue specimens from 61 NAFLD patients and 18 controls. The area under the curve of correctly classified steatosis by the algorithm was 0.970 (95% CI 0.968–0.973), P < 0.001. Accuracy of the algorithm was 91.9%, with a classification error of 8.1%. SPA correlated significantly with steatosis grade (Rs = 0.845, CI: 0.749–0.902, P < 0.001) and increased significantly with each individual steatosis grade, except between Grade 2 and 3.

Conclusions

We have developed a novel digital analysis algorithm that accurately quantifies steatosis on WSIs of liver tissue. This algorithm can be incorporated when quantification of steatosis is warranted, such as in clinical trials studying efficacy of new therapeutic interventions in NAFLD. © 2019 The Authors. Cytometry Part B: Clinical Cytometry published by Wiley Periodicals, Inc. on behalf of International Clinical Cytometry Society.

The "Skinny" on Assessment and Utilization of Steatotic Liver Grafts: A Systematic Review

The frequency at which steatotic deceased donor liver grafts are encountered will likely continue to increase. Utilization of liver grafts with moderate-to-severe steatosis for liver transplantation (LT) has been previously shown to be associated with increased rates of primary nonfunction and decreased recipient survival. In order to better inform clinical decision making and guide future research, critical evaluation of the literature on donor liver steatosis and posttransplantation outcome is needed. This literature review aims to provide the "skinny" on using deceased donor steatotic livers for LT.

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.

Controlled attenuation parameter for steatosis grading in chronic hepatitis C compared with digital morphometric analysis of liver biopsy: impact of individual elastography measurement quality

BACKGROUND AND OBJECTIVE

Controlled attenuation parameter (CAP) diagnostic performance for steatosis grading has been controversial and considerable observer-related variability in liver biopsy has been reported. This is a subanalysis of a larger chronic hepatitis C study on noninvasive fibrosis staging.

MATERIALS AND METHODS

Patients were prospectively enrolled for paired liver biopsy and transient elastography. Biopsy fragments were subjected to digital morphometric steatosis quantification. Associated patient and technical factors, including a newly described elastogram quality score, were evaluated.

RESULTS

A total of 312 patients were included in the final analysis. The mean liver stiffness was 8.7±2.1 kPa. Morphometry showed S0 in 19.2% of patients, S1 in 28.5%, S2 in 31.1%, and S3 in 21.2%. CAP showed S0 in 11.2% of patients, S1 in 26.6%, S2 in 56.7%, and S3 in 5.4%. Spearman coefficient showed a positive and independent correlation between CAP and morphometric analysis (r=0.48, P<0.05), except for distinguishing S1 and S2 (P=0.11). Area under the receiver operating characteristic curves for the presence or absence of steatosis was 0.944; differentiation between levels I, II, and III were 0.776, 0.812, and 0.879. Elastogram quality independently predicted accuracy [odds ratio (OR): 6.95, 95% confidence interval (95%CI): 4.45-9.06 as well as CAP interquartile range OR: 2.81, 95%CI: 1.67-3.99] and liver stiffness (OR: 0.78, 95%CI: 0.51-0.80).

CONCLUSION

We present an external validation for CAP against the objective steatosis quantification provided by digital morphometry. Fairly good performance indicators were found, except for S1 versus S2 differentiation. Variability and higher liver stiffness were associated with lower performance. Achieving higher quality measurements, however, overcame such limitations with excellent accuracy.

Validation of whole-slide imaging in the primary diagnosis of liver biopsies in a University Hospital

BACKGROUND

Experience in the use of whole slide imaging (WSI) for primary diagnosis is limited and there are no comprehensive reports evaluating this technology in liver biopsy specimens.

AIMS

To determine the accuracy of interpretation of WSI compared with conventional light microscopy (CLM) in the diagnosis of needle liver biopsies.

METHODS

Two experienced liver pathologists blindly analyzed 176 consecutive biopsies from the Pathology Department at the Hospital Clinic of Barcelona. One of the observers performed the initial evaluation with CLM, and the second evaluation with WSI, whereas the second observer performed the first evaluation with WSI and the second with CLM. All slides were digitized in a Ventana iScan HT at 400× and evaluated with the Virtuoso viewer (Roche diagnostics). We used kappa statistics (κ) for two observations.

RESULTS

Intra-observer agreement between WSI and CLM evaluations was almost perfect (96.6%, κ=0.9; 95% confidence interval [95% CI]: 0.9-1 for observer 1, and 90.3%, κ=0.9; 95%CI: 0.8-0.9 for observer 2). Both native and transplantation biopsies showed an almost perfect concordance in the diagnosis.

CONCLUSION

Diagnosis of needle liver biopsy specimens using WSI is accurate. This technology can reliably be introduced in routine diagnosis.

Non-alcoholic fatty liver disease: An expanded review

Non-alcoholic fatty liver disease (NAFLD) encompasses the simple steatosis to more progressive steatosis with associated hepatitis, fibrosis, cirrhosis, and in some cases hepatocellular carcinoma. NAFLD is a growing epidemic, not only in the United States, but worldwide in part due to obesity and insulin resistance leading to liver accumulation of triglycerides and free fatty acids. Numerous risk factors for the development of NAFLD have been espoused with most having some form of metabolic derangement or insulin resistance at the core of its pathophysiology. NAFLD patients are at increased risk of liver-related as well as cardiovascular mortality, and NAFLD is rapidly becoming the leading indication for liver transplantation. Liver biopsy remains the gold standard for definitive diagnosis, but the development of noninvasive advanced imaging, biochemical and genetic tests will no doubt provide future clinicians with a great deal of information and opportunity for enhanced understanding of the pathogenesis and targeted treatment. As it currently stands several medications/supplements are being used in the treatment of NAFLD; however, none seem to be the "magic bullet" in curtailing this growing problem yet. In this review we summarized the current knowledge of NAFLD epidemiology, risk factors, diagnosis, pathogenesis, pathologic changes, natural history, and treatment in order to aid in further understanding this disease and better managing NAFLD patients.

Transaminase abnormalities and adaptations of the liver lobule manifest at specific cut-offs of steatosis

There is little documented evidence suggesting that liver fat is responsible for liver injury in the absence of other disease processes. We investigated the relationships between liver fat, aminotransferases and hepatic architecture in liver biopsies with simple steatosis. We identified 136 biopsies with simple steatosis from the Royal Free Hospital Archives with both clinical data and sufficient material. Digital image analysis was employed to measure fat proportionate area (mFPA). Hepatocyte area (HA) and lobule radius (LR) were also measured. There were significant increases in ALT (p < 0.001) and AST (p = 0.013) with increased fat content and evidence to suggest both 5% and 20% mFPA as a cut-off for raised ALT. In liver with increased fat content there were significant increases in HA (p < 0.001). LR also increased as mFPA increased to 10% (p < 0.001), at which point the lobule ceased to expand further and was counterbalanced with a decrease in the number of hepatocytes per lobule (p = 0.029). Consequently there are mechanisms of adaption in the liver architecture to accommodate the accumulation of fat and these are accompanied by significant increases in transaminases. These results support the generally accepted cut-off of 5% fat for steatosis and indicate 20% as a threshold of more severe liver injury.

Age- and Gender Dependent Liver Fat Content in a Healthy Normal BMI Population as Quantified by Fat-Water Separating DIXON MR Imaging

OBJECTIVES

To establish age- and sex-dependent values of magnetic resonance (MR) liver fat-signal fraction (FSF) in healthy volunteers with normal body-mass index (BMI).

METHODS

2-point mDIXON sequences (repetition time/echo time, 4.2msec/1.2msec, 3.1msec) at 3.0 Tesla MR were acquired in 80 healthy volunteers with normal BMI (18.2 to 25.7 kg/m2) between 20 and 62 years (10 men/10 women per decade). FSF was measured in 5 liver segments (segment II, III, VI, VII, VIII) based on mean signal intensities in regions of interest placed on mDIXON-based water and fat images. Multivariate general linear models were used to test for significant differences between BMI-corrected FSF among age subgroups. Pearson and Spearman correlations between FSF and several body measures were calculated.

RESULTS

Mean FSF (%) ± standard deviations significantly differed between women (3.91 ± 1.10) and men (4.69 ± 1.38) and varied with age for women/men (p-value: 0.002/0.027): 3.05 ± 0.49/3.74 ± 0.60 (age group 20-29), 3.75 ± 0.66/4.99 ± 1.30 (30-39), 4.76 ± 1.16/5.25 ± 1.97 (40-49) and 4.09 ± 1.26/4.79 ± 0.93 (50-62). FSF differences among age subgroups were significant for women only (p = 0.003).

CONCLUSIONS

MR-based liver fat content is higher in men and peaks in the fifth decade for both genders.

In vivo assessment of diet-induced rat hepatic steatosis development by percutaneous single-fiber spectroscopy detects scattering spectral changes due to fatty infiltration

This study explores percutaneous single-fiber spectroscopy (SfS) of rat livers undergoing fatty infiltration. Eight test rats were fed a methionine-choline-deficient (MCD) diet, and four control rats were fed a normal diet. Two test rats and one control rat were euthanized on days 12, 28, 49, and 77 following initiation of the diet, after percutaneous SfS of the liver under transabdominal ultrasound guidance. Histology of each set of the two euthanized test rats showed mild and mild hepatic lipid accumulations on day 12, moderate and severe on day 28, severe and mild on day 49, and moderate and mild on day 77. Livers with moderate or higher lipid accumulation generally presented higher spectral reflectance intensity when compared to lean livers. Livers of the eight test rats on day 12, two of which had mild lipid accumulation, revealed an average scattering power of 0.37±0.14 in comparison to 0.07±0.14 for the four control rats (p<0.01 ). When livers of the test rats with various levels of fatty infiltration were combined, the average scattering power was 0.36±0.15 0.36±0.15 in comparison to 0.14±0.24 of the control rats (0.05<p<0.1). Increasing lipid accumulation in concentration and size seemed to cause an increase of the scattering power prior to increasing total spectral reflectance.

Pathology of alcoholic liver disease, can it be differentiated from nonalcoholic steatohepatitis?

The liver involvement in alcoholic liver disease (ALD) classically ranges from alcoholic steatosis, alcoholic hepatitis or steatohepatitis, alcoholic cirrhosis and even hepatocellular carcinoma. The more commonly seen histologic features include macrovesicular steatosis, neutrophilic lobular inflammation, ballooning degeneration, Mallory-Denk bodies, portal and pericellular fibrosis. Nonalcoholic steatohepatitis (NASH) is a condition with similar histology in the absence of a history of alcohol intake. Although the distinction is essentially based on presence or absence of a history of significant alcohol intake, certain histologic features favour one or the other diagnosis. This review aims at describing the histologic spectrum of alcoholic liver disease and at highlighting the histologic differences between ALD and NASH.

The use of guideline images to improve histological estimation of hepatic steatosis

BACKGROUND & AIMS

Guideline images of specific fat proportionate area (FPA) percentages have recently been published to aid the histological assessment of liver steatosis as subjective estimates of FPA are usually overestimated. To assess, (i) the effect of guideline images on accuracy and concordance of estimated FPA (eFPA), (ii) experience of steatosis grading systems on eFPA, (iii) the effect of magnification on assessment of FPA (iv) and produce a range of guideline images at x4 objective magnification (OM).

METHODS

Two circulations of sample images (C1 and C2) were circulated to UK liver external quality assessment histopathology scheme members who were asked to independently evaluate steatosis. Each circulation consisted of 15 images taken at both x20 and x4OM representing the full range of steatosis. C1 was distributed first, then C2 with guideline images of FPA 6 weeks later.

RESULTS

Participants overestimated FPA in C1. In C2, there was significant improvement in accuracy (P < 0.001) of eFPA for sample images with mFPA >5%. Concordance of x4OM eFPA was substantial in both circulations (C1 K = 0.878, C2 K = 0.724).

CONCLUSION

The tendency to overestimate eFPA has been corroborated and can be largely corrected with the use of guideline images (without needing digital image analysis). There is a need to redefine steatosis grades that are clinically significant and validated using an accurate quantification of steatosis.

The impact of obesity on liver histology

Obesity and insulin resistance produce alterations in the liver's normal role in lipid metabolism resulting in a sequence of changes recognizable on liver biopsy. Hepatocellular fat vacuoles increase with BMI, producing steatosis. Steatohepatitis occurs when there is also cytoskeletal damage with loss of keratin filaments, ballooning of affected liver cells and formation of Mallory-Denk bodies. Activation of hepatic stellate cells produces fibrosis in the perisinusoidal spaces. With continuing fibrogenesis there is progression to bridging fibrosis and cirrhosis. Hepatocellular carcinoma may develop in the cirrhotic liver, but both hepatocellular adenoma and hepatocellular carcinoma may occur in pre-cirrhotic fatty liver disease.

Limited correlation between conventional pathologist and automatic computer-assisted quantification of hepatic steatosis due to difference between event-based and surface-based analysis

Computer-assisted automatic quantification (CAQ) was developed as an alternative method for the diagnosis of hepatic steatosis in order to compensate for observer-dependent bias. Here, we aim to demonstrate that CAQ can provide an accurate and precise result in analysis of fatty content, but that it is inappropriate to validate CAQ by comparison with conventional pathologist estimation (PE). Male rats were fed with a methionine-choline-deficient plus high-fat diet for three days, one week, or two weeks to induce mild, moderate, or severe steatosis. Samples were collected from all liver lobes. Severity of hepatic steatosis was assessed by an experienced pathologist who estimated the percentage of hepatocytes containing lipid droplets. Fatty content was quantified by PE, CAQ, and biochemical analysis (BA). CAQ, PE, and BA can correctly reflect severe fatty change. However, in the case of mild and moderate steatosis, PE could not reflect the true fatty content ( r between PE and BA was <0). The result of CAQ correlated well with that of BA among the various degrees of severity of hepatic steatosis. In conclusion, due to a difference between event-based and surface-based analysis, it is inappropriate to validate the CAQ of hepatic steatosis by comparison with PE.