Liver steatosis assessment: correlations among pathology, radiology, clinical data and automated image analysis software

Comprehensive Evaluation of Human Donor Liver Viability with Polarization-Sensitive Optical Coherence Tomography

Human liver transplantation is severely constrained by a critical shortage of donor livers, with approximately one quarter of patients on the waiting list dying due to the scarcity of viable organs. Current liver viability assessments, which rely on invasive pathological methods, are hampered by limited sampling from biopsies, particularly in marginal livers from extended criteria donors (ECD) intended to expand the donor pool. Consequently, there is a pressing need for more comprehensive and non-invasive evaluation techniques to meet the escalating demand for liver transplants. In this study, we propose the use of polarization-sensitive optical coherence tomography (PS-OCT) to perform a thorough viability evaluation across the entire surface of donor livers. PS-OCT imaging was conducted on multiple regions, achieving near-complete coverage of the liver surface, and the findings were cross-validated with histopathological evaluations. The analysis of hepatic parameters derived from pathology highlighted tissue heterogeneity. Leveraging machine learning and texture analysis, we quantified hepatic steatosis, fibrosis, inflammation, and necrosis, and established strong correlations (≥ 80%) between PS-OCT quantifications and pathological assessments. PS-OCT offers a non-invasive assessment of liver viability by quantifying hepatic parenchymal parameters across the entire donor liver, significantly complementing current pathological analysis. These results suggest that PS-OCT provides a robust, non-invasive approach to assessing donor liver viability, which could potentially decrease the discard rate of higher risk livers, thereby expanding the donor pool and reducing the inadvertent use of those livers unsuitable for transplantation.

Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD) and Thyroid Function in Childhood Obesity: A Vicious Circle?

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a multisystem disorder characterized by the presence of fatty liver degeneration associated with excess adiposity or prediabetes/type 2 diabetes or metabolic dysregulation. An intricate relationship between the liver and thyroid has been reported in both health and disease. Simultaneously, there is a strong correlation between obesity and both MAFLD and thyroid dysfunction. In this narrative review, we highlighted the relationship between MAFLD and thyroid function in children and adolescents with obesity in order to explore how thyroid hormones (THs) act as predisposing factors in the onset, progression, and sustainability of MAFLD. THs are integral to the intricate balance of metabolic activities, ensuring energy homeostasis, and are indispensable for growth and development. Regarding liver homeostasis, THs have been suggested to interact with liver lipid homeostasis through a series of processes, including stimulating the entry of free fatty acids into the liver for esterification into triglycerides and increasing mitochondrial β-oxidation of fatty acids to impact hepatic lipid accumulation. The literature supports a correlation between MAFLD and obesity, THs and obesity, and MAFLD and THs; however, results in the pediatric population are very limited. Even though the underlying pathogenic mechanism involved in the relationship between MAFLD and thyroid function remains not fully elucidated, the role of THs as predisposing factors of MAFLD could be postulated. A potential vicious circle among these three conditions cannot be excluded. Identifying novel elements that may contribute to MAFLD could offer a practical approach to assessing children at risk of developing the condition.

Object detection: A novel AI technology for the diagnosis of hepatocyte ballooning

Metabolic dysfunction-associated fatty liver disease (MAFLD) has reached epidemic proportions worldwide and is the most frequent cause of chronic liver disease in developed countries. Within the spectrum of liver disease in MAFLD, steatohepatitis is a progressive form of liver disease and hepatocyte ballooning (HB) is a cardinal pathological feature of steatohepatitis. The accurate and reproducible diagnosis of HB is therefore critical for the early detection and treatment of steatohepatitis. Currently, a diagnosis of HB relies on pathological examination by expert pathologists, which may be a time-consuming and subjective process. Hence, there has been interest in developing automated methods for diagnosing HB. This narrative review briefly discusses the development of artificial intelligence (AI) technology for diagnosing fatty liver disease pathology over the last 30 years and provides an overview of the current research status of AI algorithms for the identification of HB, including published articles on traditional machine learning algorithms and deep learning algorithms. This narrative review also provides a summary of object detection algorithms, including the principles, historical developments, and applications in the medical image analysis. The potential benefits of object detection algorithms for HB diagnosis (specifically those combined with a transformer architecture) are discussed, along with the future directions of object detection algorithms in HB diagnosis and the potential applications of generative AI on transformer architecture in this field. In conclusion, object detection algorithms have huge potential for the identification of HB and could make the diagnosis of MAFLD more accurate and efficient in the near future.

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.

Study protocol for a randomized, controlled trial using a novel, family-centered diet treatment to prevent nonalcoholic fatty liver disease in Hispanic children

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is the leading liver disorder among U.S. children and is most prevalent among Hispanic children with obesity. Previous research has shown that reducing the consumption of free sugars (added sugars + naturally occurring sugars in fruit juice) can reverse liver steatosis in adolescents with NAFLD. This study aims to determine if a low-free sugar diet (LFSD) can prevent liver fat accumulation and NAFLD in high-risk children.

METHODS

In this randomized controlled trial, we will enroll 140 Hispanic children aged 6 to 9 years who are ≥50th percentile BMI and without a previous diagnosis of NAFLD. Participants will be randomly assigned to either an experimental (LFSD) or a control (usual diet + educational materials) group. The one-year intervention includes removal of foods high in free sugars from the home at baseline, provision of LFSD household groceries for the entire family (weeks 1-4, 12, 24, and 36), dietitian-guided family grocery shopping sessions (weeks 12, 24, and 36), and ongoing education and motivational interviewing to promote LFSD. Both groups complete assessment measures at baseline, 6, 12, 18, and 24 months. Primary study outcomes are percent hepatic fat at 12 months and incidence of clinically significant hepatic steatosis (>5%) + elevated liver enzymes at 24 months. Secondary outcomes include metabolic markers potentially mediating or moderating NAFLD pathogenesis.

DISCUSSION

This protocol describes the rationale, eligibility criteria, recruitment strategies, analysis plan as well as a novel dietary intervention design. Study results will inform future dietary guidelines for pediatric NAFLD prevention.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT05292352.

Possible prediction of obesity-related liver disease in children and adolescents using indices of body composition

BACKGROUND

Diagnosis of nonalcoholic fatty liver disease in children and adolescents currently requires advanced or invasive technologies.

OBJECTIVES

We aimed to develop a method to improve diagnosis, using body composition indices and liver biochemical markers.

METHODS

To diagnose non-alcoholic fatty liver disease, 767 Danish children and adolescents underwent clinical examination, blood sampling, whole-body dual-energy X-ray absorptiometry scanning and proton magnetic resonance spectroscopy for liver fat quantification. Fourteen variables were selected as a starting point to construct models, narrowed by stepwise selection. Individuals were split into a training set for model construction and a validation test set. The final models were applied to 2120 Danish children and adolescents to estimate the prevalence.

RESULTS

The final models included five variables in different combinations: body mass index-standard deviation score, android-to-gynoid-fat ratio, android-regional fat percent, trunk-regional fat percent and alanine transaminase. When validated, the sensitivity and specificity ranged from 38.6% to 51.7% and 87.6% to 91.9%, respectively. The estimated prevalence was 24.2%-35.3%. Models including alanine transaminase alongside body composition measurements displayed higher sensitivity.

CONCLUSIONS

Body composition indices and alanine transaminase can be used to estimate non-alcoholic fatty liver disease, with 38.6%-51.7% sensitivity and 87.6%-91.9%, specificity, in children and adolescents with overweight (including obesity). These estimated a 24.2%-35.3% prevalence in 2120 patients.

Development of a Scoring System to Differentiate Amiodarone-Induced Liver Injury From Alcoholic Steatohepatitis

OBJECTIVES

Amiodarone-induced liver injury (AILI) is histopathologically similar to alcoholic steatohepatitis (ASH). We sought to elucidate their histologic differences and develop a scoring system to differentiate these two entities.

METHODS

A cohort of 17 AILI and 17 ASH cases was included in the initial study. Cases from three different institutions were included for further validation.

RESULTS

Macrovesicular steatosis was usually below 10% of the liver parenchyma in AILI. Hepatocyte ballooning degeneration was more common in ASH than in AILI. "Balloon-like" hepatocyte was more common in AILI than in ASH. Lobular neutrophilic inflammation, satellitosis, and cholestasis were more common in ASH. Mallory-Denk bodies and pericellular fibrosis in AILI were mainly located in zone 1 compared with a panacinar or zone 3 distribution in ASH. A scoring system was developed in which points were assigned to different histologic features; a total sum of less than 5 suggests AILI, more than 5 is ASH, and 5 is equivocal. This scoring system was then evaluated on a test cohort comprising 14 AILI cases, in which 13 cases were correctly assigned with a score less than 5. The sensitivity, specificity, and accuracy for diagnosing AILI in the test cohort were 92.9%, 91.7%, and 92.3%, respectively.

CONCLUSIONS

This scoring system can aid pathologists to differentiate AILI from ASH.

Machine Learning Applications in Solid Organ Transplantation and Related Complications

The complexity of transplant medicine pushes the boundaries of innate, human reasoning. From networks of immune modulators to dynamic pharmacokinetics to variable postoperative graft survival to equitable allocation of scarce organs, machine learning promises to inform clinical decision making by deciphering prodigious amounts of available data. This paper reviews current research describing how algorithms have the potential to augment clinical practice in solid organ transplantation. We provide a general introduction to different machine learning techniques, describing their strengths, limitations, and barriers to clinical implementation. We summarize emerging evidence that recent advances that allow machine learning algorithms to predict acute post-surgical and long-term outcomes, classify biopsy and radiographic data, augment pharmacologic decision making, and accurately represent the complexity of host immune response. Yet, many of these applications exist in pre-clinical form only, supported primarily by evidence of single-center, retrospective studies. Prospective investigation of these technologies has the potential to unlock the potential of machine learning to augment solid organ transplantation clinical care and health care delivery systems.

Defining paediatric metabolic (dysfunction)-associated fatty liver disease: an international expert consensus statement

The term non-alcoholic fatty liver disease (NAFLD), and its definition, have limitations for both adults and children. The definition is most problematic for children, for whom alcohol consumption is usually not a concern. This problematic definition has prompted a consensus to rename and redefine adult NAFLD associated with metabolic dysregulation to metabolic (dysfunction)-associated fatty liver disease (MAFLD). Similarities, distinctions, and differences exist in the causes, natural history, and prognosis of fatty liver diseases in children compared with adults. In this Viewpoint we, an international panel, propose an overarching framework for paediatric fatty liver diseases and an age-appropriate MAFLD definition based on sex and age percentiles. The framework recognises the possibility of other coexisting systemic fatty liver diseases in children. The new MAFLD diagnostic criteria provide paediatricians with a conceptual scaffold for disease diagnosis, risk stratification, and improved clinical and multidisciplinary care, and they align with a definition that is valid across the lifespan.

State of machine and deep learning in histopathological applications in digestive diseases

Machine learning (ML)- and deep learning (DL)-based imaging modalities have exhibited the capacity to handle extremely high dimensional data for a number of computer vision tasks. While these approaches have been applied to numerous data types, this capacity can be especially leveraged by application on histopathological images, which capture cellular and structural features with their high-resolution, microscopic perspectives. Already, these methodologies have demonstrated promising performance in a variety of applications like disease classification, cancer grading, structure and cellular localizations, and prognostic predictions. A wide range of pathologies requiring histopathological evaluation exist in gastroenterology and hepatology, indicating these as disciplines highly targetable for integration of these technologies. Gastroenterologists have also already been primed to consider the impact of these algorithms, as development of real-time endoscopic video analysis software has been an active and popular field of research. This heightened clinical awareness will likely be important for future integration of these methods and to drive interdisciplinary collaborations on emerging studies. To provide an overview on the application of these methodologies for gastrointestinal and hepatological histopathological slides, this review will discuss general ML and DL concepts, introduce recent and emerging literature using these methods, and cover challenges moving forward to further advance the field.

Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples

Whole slide imaging, which is an important technique in the field of digital pathology, has recently been the subject of increased interest and avenues for utilisation, and with more widespread whole slide image (WSI) utilisation, there will also be increased interest in and implementation of image analysis (IA) techniques. IA includes artificial intelligence (AI) and targeted or hypothesis-driven algorithms. In the overall pathology field, the number of citations related to these topics has increased in recent years. Renal pathology is one anatomical pathology subspecialty that has utilised WSIs and IA algorithms; it can be argued that renal transplant pathology could be particularly suited for whole slide imaging and IA, as renal transplant pathology is frequently classified by use of the semiquantitative Banff classification of renal allograft pathology. Hypothesis-driven/targeted algorithms have been used in the past for the assessment of a variety of features in the kidney (e.g. interstitial fibrosis, tubular atrophy, inflammation); in recent years, the amount of research has particularly increased in the area of AI/machine learning for the identification of glomeruli, for histological segmentation, and for other applications. Deep learning is the form of machine learning that is most often used for such AI approaches to the 'big data' of pathology WSIs, and deep learning methods such as artificial neural networks (ANNs)/convolutional neural networks (CNNs) are utilised. Unsupervised and supervised AI algorithms can be employed to accomplish image or semantic classification. In this review, AI and other IA algorithms applied to WSIs are discussed, and examples from renal pathology are covered, with an emphasis on renal transplant pathology.

Relationship Between Histological Features of Non-alcoholic Fatty Liver Disease and Ectopic Fat on Magnetic Resonance Imaging in Children and Adolescents

Objectives: To investigate the association between ectopic fat content in the liver and pancreas, obesity-related metabolic components, and histological findings of non-alcoholic fatty liver disease (NAFLD) in children. Methods: This cross-sectional study investigated 63 children with biopsy-proven NAFLD who underwent magnetic resonance imaging (MRI), anthropometry, laboratory tests, and body composition analysis. Clinical and metabolic parameters, MRI-measured hepatic fat fraction (HFF) and pancreatic fat fraction (PFF), and histological findings were analyzed. Results: In a total of 63 children (48 boys, median age 12.6 years, median body mass index z-score 2.54), HFF was associated with histological steatosis [10.4, 23.7, and 31.1% in each steatosis grade, P < 0.001; Spearman's rho coefficient (rs) = 0.676; P < 0.001] and NAFLD activity score (rs = 0.470, P < 0.001), but not with lobular inflammation, hepatocyte ballooning, and hepatic fibrosis. PFF was not associated with any histological features of the liver. Waist circumference-to-height ratio and body fat percentage were associated with the steatosis grade (P = 0.006 and P = 0.004, respectively). Alanine aminotransferase was not associated with steatosis but was associated with lobular inflammation (P = 0.008). Lobular inflammation was also associated with high total cholesterol and low-density lipoprotein cholesterol and metabolic syndrome (P = 0.015, P = 0.036, and P = 0.038, respectively). Conclusions: Hepatic steatosis on MRI was only associated with the histological steatosis grade, while elevated serum levels of liver enzymes and lipids were related to the severity of lobular inflammation. Therefore, MRI should be interpreted in conjunction with the anthropometric and laboratory findings in pediatric patients.

Deep-learning-based accurate hepatic steatosis quantification for histological assessment of liver biopsies

Hepatic steatosis droplet quantification with histology biopsies has high clinical significance for risk stratification and management of patients with fatty liver diseases and in the decision to use donor livers for transplantation. However, pathology reviewing processes, when conducted manually, are subject to a high inter- and intra-reader variability, due to the overwhelmingly large number and significantly varying appearance of steatosis instances. This process is challenging as there is a large number of overlapped steatosis droplets with either missing or weak boundaries. In this study, we propose a deep-learning-based region-boundary integrated network for precise steatosis quantification with whole slide liver histopathology images. The proposed model consists of two sequential steps: a region extraction and a boundary prediction module for foreground regions and steatosis boundary prediction, followed by an integrated prediction map generation. Missing steatosis boundaries are next recovered from the predicted map and assembled from adjacent image patches to generate results for the whole slide histopathology image. The resulting steatosis measures both at the pixel level and steatosis object-level present strong correlation with pathologist annotations, radiology readouts and clinical data. In addition, the segregated steatosis object count is shown as a promising alternative measure to the traditional metrics at the pixel level. These results suggest a high potential of artificial intelligence-assisted technology to enhance liver disease decision support using whole slide images.

Quantitative assessment of liver fibrosis by digital image analysis reveals correlation with qualitative clinical fibrosis staging in liver transplant patients

Technologies for digitizing tissues provide important quantitative data for liver histopathology investigation. We aimed to assess liver fibrosis degree with quantitative morphometric measurements of histopathological sections utilizing digital image analysis (DIA) and to further investigate if a correlation with histopathologic scoring (Scheuer staging) exists. A retrospective study of patients with at least two post-liver transplant biopsies having a Scheuer stage of ≤ 2 at baseline were gathered. Portal tract fibrotic percentage (%) and size (μm²) were measured by DIA, while clinical fibrosis score was measured by the Scheuer system. Correlations between DIA measurements and Scheuer scores were computed by Spearman correlation analysis. Differences between mean levels of fibrosis (score, size, and percentage) at baseline versus second visit were computed by Student’s t-test. P values < 0.05 were considered significant. Of 22 patients who met the study criteria, 54 biopsies were included for analysis. Average levels ±standard error [S.E.] of portal tract fibrotic percentage (%) and size (μm²) progressed from 46.5 ± 3.6% at baseline to 61.8 ± 3.8% at the second visit (P = 0.005 by Student’s t-test), and from 28,075 ± 3,232 μm² at base line to 67,146 ± 10,639 μm² at the second visit (P = 0.002 by Student’s t-test), respectively. Average levels of Scheuer fibrosis scores progressed from 0.55±0.19 at baseline to 1.14±0.26 at the second visit (P = 0.02 by Student’s t-test). Portal tract fibrotic percentage (%) and portal tract fibrotic size were directly correlated with clinical Scheuer fibrosis stage, with Spearman correlation coefficient and P value computed as r = 0.70, P < 0.0001 and r = 0.41, P = 0.002, respectively. Digital quantitative assessment of portal triad size and fibrosis percentage demonstrates a strong correlation with visually assessed histologic stage of liver fibrosis and complements the standard assessment for allograft monitoring, suggesting the utility of future WSI analysis.

Deep learning quantification of percent steatosis in donor liver biopsy frozen sections

Background

Pathologist evaluation of donor liver biopsies provides information for accepting or discarding potential donor livers. Due to the urgent nature of the decision process, this is regularly performed using frozen sectioning at the time of biopsy. The percent steatosis in a donor liver biopsy correlates with transplant outcome, however there is significant inter- and intra-observer variability in quantifying steatosis, compounded by frozen section artifact. We hypothesized that a deep learning model could identify and quantify steatosis in donor liver biopsies.

Methods

We developed a deep learning convolutional neural network that generates a steatosis probability map from an input whole slide image (WSI) of a hematoxylin and eosin-stained frozen section, and subsequently calculates the percent steatosis. Ninety-six WSI of frozen donor liver sections from our transplant pathology service were annotated for steatosis and used to train (n = 30 WSI) and test (n = 66 WSI) the deep learning model.

Findings

The model had good correlation and agreement with the annotation in both the training set (r of 0.88, intraclass correlation coefficient [ICC] of 0.88) and novel input test sets (r = 0.85 and ICC=0.85). These measurements were superior to the estimates of the on-service pathologist at the time of initial evaluation (r = 0.52 and ICC=0.52 for the training set, and r = 0.74 and ICC=0.72 for the test set).

Interpretation

Use of this deep learning algorithm could be incorporated into routine pathology workflows for fast, accurate, and reproducible donor liver evaluation.

Funding

Mid-America Transplant Society

Banff Digital Pathology Working Group: Going digital in transplant pathology

The Banff Digital Pathology Working Group (DPWG) was formed in the time leading up to and during the joint American Society for Histocompatibility and Immunogenetics/Banff Meeting, September 23-27, 2019, held in Pittsburgh, Pennsylvania. At the meeting, the 14th Banff Conference, presentations directly and peripherally related to the topic of "digital pathology" were presented; and discussions before, during, and after the meeting have resulted in a list of issues to address for the DPWG. Included are practice standardization, integrative approaches for study classification, scoring of histologic parameters (eg, interstitial fibrosis and tubular atrophy and inflammation), algorithm classification, and precision diagnosis (eg, molecular pathways and therapeutics). Since the meeting, a survey with international participation of mostly pathologists (81%) was conducted, showing that whole slide imaging is available at the majority of centers (71%) but that artificial intelligence (AI)/machine learning was only used in ≈12% of centers, with a wide variety of programs/algorithms employed. Digitalization is not just an end in itself. It also is a necessary precondition for AI and other approaches. Discussions at the meeting and the survey highlight the unmet need for a Banff DPWG and point the way toward future contributions that can be made.

Utility of MR proton density fat fraction and its correlation with ultrasonography and biochemical markers in nonalcoholic fatty liver disease in overweight adolescents

Background Clinical or biochemical markers that have good correlation with magnetic resonance proton density fat fraction (MR PDFF) can be used as simple tools for the screening for nonalcoholic fatty liver disease (NAFLD) and in determining the degree of fatty infiltration of the liver. The objective of this study was to determine the degree of relationship between MR PDFF and ultrasonography (USG) grades of fatty liver, and clinical and biochemical parameters of adolescents and to determine the sensitivity and specificity of USG for diagnosis of NAFLD. Methods This prospective study included 34 overweight adolescents (mean age, 12.1 ± 1.5 years; range, 10-15.1 years; 10 girls and 24 boys) who underwent both USG and magnetic resonance imaging (MRI). Correlation analysis was performed between MR fat fraction and USG grades of fatty liver, and clinical and biochemical parameters of fatty liver disease. Results MR fat fraction had a moderate positive correlation with serum alanine transaminase (ALT) and aspartate transaminase (AST) (ρ = 0.634, p < 0.001, ρ = 0.516, p = 0.002, respectively) and had a negligible or weak correlation with body mass index (BMI), BMI standard deviation score (SDS), waist circumference (WC), fasting insulin, homeostatic model assessment of insulin resistance (HOMA-IR), serum triglyceride, low-density lipoprotein (LDL), high-density lipoprotein (HDL) and total cholesterol levels. The sensitivity and specificity of USG in the diagnosis of NAFLD were 81% (95% confidence interval 54%-95%) and 50% (27%-73%), respectively. The MR fat fraction had a moderate positive correlation with ultrasound grades of fatty liver (ρ = 0.487, p = 0.003). Conclusions Serum ALT and AST are potential biochemical markers to assess the degree of hepatic steatosis in NAFLD, which needs validation in further studies. USG can be used as a screening tool for NAFLD, but the diagnosis should be confirmed by estimating the MR fat fraction.

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.

Digital Microscopy, Image Analysis, and Virtual Slide Repository

Advancements in technology and digitization have ushered in novel ways of enhancing tissue-based research via digital microscopy and image analysis. Whole slide imaging scanners enable digitization of histology slides to be stored in virtual slide repositories and to be viewed via computers instead of microscopes. Easier and faster sharing of histologic images for teaching and consultation, improved storage and preservation of quality of stained slides, and annotation of features of interest in the digital slides are just a few of the advantages of this technology. Combined with the development of software for digital image analysis, digital slides further pave the way for the development of tools that extract quantitative data from tissue-based studies. This review introduces digital microscopy and pathology, and addresses technical and scientific considerations in slide scanning, quantitative image analysis, and slide repositories. It also highlights the current state of the technology and factors that need to be taken into account to insure optimal utility, including preanalytical considerations and the importance of involving a pathologist in all major steps along the digital microscopy and pathology workflow.

A promising therapeutic option for diabetic bladder dysfunction: Adipose tissue-derived stem cells pretreated by defocused low-energy shock wave

Adipose tissue-derived stem cells (ADSCs) have shown effectiveness in treating diabetic bladder dysfunction (DBD). In the present study, ADSCs pretreated by defocused low-energy shock wave (DLSW) were first used to achieve better therapeutic effect. ADSCs were treated by DLSW prior to each passage. Secretions of vascular endothelial growth factor (VEGF) and nerve growth factor (NGF) were tested. Proliferation ability was examined by staining 5-ethynyl-2-deoxyuridine (EdU) and assessing expressions of proliferating cell nuclear antigen (PCNA) and Ki67. DBD rat model was created and subgrouped via therapeutic options of phosphate-buffered saline, ADSCs, pretreated ADSCs, and ADSCs lysate. Afterward, voiding functions were evaluated, and tissues were examined by histology. Neonatal rats received intraperitoneal injection of EdU. All rats were subgrouped and treated as narrated above. Bladder tissues were stained with EdU, Stro-1, and CD34. Results showed that shocked ADSCs were activated by secreting more VEGF and NGF, by higher EdU-retaining cells ratios, and by higher expressions of PCNA and Ki67 compared with unshocked ADSCs. Shocked ADSCs had the most effective efficacy in treating DBD by secreting the most VEGF and NGF to accelerate regenerations of revascularization and innervation. Migrations of EdU⁺ Stro-1⁺ CD34^- endogenous stem cells to bladders were enhanced by injecting ADSCs. In conclusion, ADSCs pretreated by DLSW had potent therapeutic effect in treating DBD by secreting VEGF and NGF. Recruitment of endogenous stem cells was considered as an important mechanism in this regenerative process.

LIVER STEATOSIS SEGMENTATION WITH DEEP LEARNING METHODS

Liver steatosis is known as the abnormal accumulation of lipids within cells. An accurate quantification of steatosis area within the liver histopathological microscopy images plays an important role in liver disease diagnosis and transplantation assessment. Such a quantification analysis often requires a precise steatosis segmentation that is challenging due to abundant presence of highly overlapped steatosis droplets. In this paper, a deep learning model Mask-RCNN is used to segment the steatosis droplets in clumps. Extended from Faster R-CNN, Mask-RCNN can predict object masks in addition to bounding box detection. With transfer learning, the resulting model is able to segment overlapped steatosis regions at 75.87% by Average Precision, 60.66% by Recall,65.88% by F1-score, and 76.97% by Jaccard index, promising to support liver disease diagnosis and allograft rejection prediction in future clinical practice.

Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association

The advent of whole-slide imaging in digital pathology has brought about the advancement of computer-aided examination of tissue via digital image analysis. Digitized slides can now be easily annotated and analyzed via a variety of algorithms. This study reviews the fundamentals of tissue image analysis and aims to provide pathologists with basic information regarding the features, applications, and general workflow of these new tools. The review gives an overview of the basic categories of software solutions available, potential analysis strategies, technical considerations, and general algorithm readouts. Advantages and limitations of tissue image analysis are discussed, and emerging concepts, such as artificial intelligence and machine learning, are introduced. Finally, examples of how digital image analysis tools are currently being used in diagnostic laboratories, translational research, and drug development are discussed.

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.

Quantification of hepatic steatosis in histologic images by deep learning method

OBJECTIVE

To develop and test a novel method for automatic quantification of hepatic steatosis in histologic images based on the deep learning scheme designed to predict the fat ratio directly, which aims to improve accuracy in diagnosis of non-alcoholic fatty liver disease (NAFLD) with objective assessment of the severity of hepatic steatosis instead of subjective visual estimation.

MATERIALS AND METHODS

Thirty-six 8-week old New Zealand white rabbits of both sexes were fed with high-cholesterol, high-fat diet and sacrificed under deep anesthesia at various time points to obtain the pathological specimen. All rabbits were performed by multislice computed tomography for surveillance to measure density changes of liver parenchyma. A deep learning scheme using a convolutional neural network was developed to directly predict the liver fat ratio based on the pathological images. The average error value, standard deviation, and accuracy (error <5%) were evaluated and compared between the deep learning scheme and manual segmentation results. The Pearson's correlation coefficient was also calculated in this study.

RESULTS

The deep learning scheme performs successfully on rabbit liver histologic data, showing a high degree of accuracy and stability. The average error value, standard deviation, and accuracy (error <5%) were 3.21%, 4.02%, and 79.10% for the cropped images, 2.22%, 1.92%, and 88.34% for the original images, respectively. The strong positive correlation was also observed for cropped images (R = 0.9227) and original images (R = 0.9255) in comparison to labeled fat ratio.

CONCLUSIONS

This new deep learning scheme may aid in the quantification of steatosis in the liver and facilitate its treatment by providing an earlier clinical diagnosis.

Focused scores enable reliable discrimination of small differences in steatosis

Background

Automated image analysis enables quantitative measurement of steatosis in histological images. However, spatial heterogeneity of steatosis can make quantitative steatosis scores unreliable. To improve the reliability, we have developed novel scores that are “focused” on steatotic tissue areas.

Methods

Focused scores use concepts of tile-based hotspot analysis in order to compute statistics about steatotic tissue areas in an objective way. We evaluated focused scores on three data sets of images of rodent liver sections exhibiting different amounts of dietary-induced steatosis. The same evaluation was conducted with the standard steatosis score computed by most image analysis methods.

Results

The standard score reliably discriminated large differences in steatosis (intraclass correlation coefficient ICC = 0.86), but failed to discriminate small (ICC = 0.54) and very small (ICC = 0.14) differences. With an appropriate tile size, mean-based focused scores reliably discriminated large (ICC = 0.92), small (ICC = 0.86) and very small (ICC = 0.83) differences. Focused scores based on high percentiles showed promise in further improving the discrimination of very small differences (ICC = 0.93).

Conclusions

Focused scores enable reliable discrimination of small differences in steatosis in histological images. They are conceptually simple and straightforward to use in research studies.

Perspective review on solid-organ transplant: needs in point-of-care optical biomarkers

Solid-organ transplant is one of the most complex areas of modern medicine involving surgery. There are challenging opportunities in solid-organ transplant, specifically regarding the deficiencies in pathology workflow or gaps in pathology support, which may await alleviations or even de novo solutions, by means of point-of-care, or point-of-procedure optical biomarkers. Focusing the discussions of pathology workflow on donor liver assessment, we analyze the undermet need for intraoperative, real-time, and nondestructive assessment of the donor injuries (such as fibrosis, steatosis, and necrosis) that are the most significant predictors of post-transplant viability. We also identify an unmet need for real-time and nondestructive characterization of ischemia or irreversible injuries to the donor liver, earlier than appearing on morphological histology examined with light microscopy. Point-of-procedure laparoscopic optical biomarkers of liver injuries and tissue ischemia may also facilitate post-transplant management that is currently difficult for or devoid of pathological consultation due to lack of tools. The potential and pitfalls of point-of-procedure optical biomarkers for liver assessment are exemplified in breadth for steatosis. The more general and overarching challenges of point-of-procedure optical biomarkers for liver transplant pathology, including the shielding effect of the liver capsule that was quantitated only recently, are projected. The technological and presentational benchmarks that a candidate technology of point-of-procedure optical biomarkers for transplant pathology must demonstrate to motivate clinical translation are also foreseen.

In vivo percutaneous reflectance spectroscopy of fatty liver development in rats suggests that the elevation of the scattering power is an early indicator of hepatic steatosis

This study assessed whether there was a scattering spectral marker quantifiable by reflectance measurements that could indicate early development of hepatic steatosis in rats for potential applications to pre-procurement organ evaluation. Sixteen rats were fed a methionine-choline-deficient (MCD) diet and eight rats were fed a normal diet. Direct assessment of the liver parenchyma of rats in vivo was performed by percutaneous reflectance spectroscopy using a single fiber probe at the beginning of diet-intake and arbitrary post-diet-intake times up to 11 weeks to render longitudinal comparison. Histological sampling of the liver over the duration of diet administration was performed on two MCD-diet treated rats and one control rat euthanized after reflectance spectroscopy measurement. The images of hematoxylin/eosin-stained liver specimens were analyzed morphometrically to evaluate the lipid size changes associated with the level of steatosis. The MCD-diet-treated group ([Formula: see text]) had mild steatosis in seven rats, moderate in three rats, severe in six rats, and no other significant pathology. No control rats ([Formula: see text]) developed hepatic steatosis. Among the parameters retrieved from per-SfS, only the scattering power (can be either positive or negative) appeared to be statistically different between MCD-treated and control livers. The scattering power for the 16 MCD-diet-treated livers at the time of euthanasia and presenting various levels of steatosis was [Formula: see text], in comparison to [Formula: see text] of the eight control livers [Formula: see text]. When evaluated at days 12 and 13 combined, the scattering power of the 16 MCD-diet-treated livers was [Formula: see text], in comparison to [Formula: see text] of the eight control livers ([Formula: see text]). All of four MCD-treated livers harvested at days 12 and 13 presented mild steatosis with sub-micron size lipid droplets, even though none of the MCD-treated livers were sonographically remarkable for fatty changes. The elevation of the scattering power may be a valuable marker indicating early hepatic steatosis before the steatosis is sonographically detectable.

Automated quantification of steatosis: agreement with stereological point counting

BACKGROUND

Steatosis is routinely assessed histologically in clinical practice and research. Automated image analysis can reduce the effort of quantifying steatosis. Since reproducibility is essential for practical use, we have evaluated different analysis methods in terms of their agreement with stereological point counting (SPC) performed by a hepatologist.

METHODS

The evaluation was based on a large and representative data set of 970 histological images from human patients with different liver diseases. Three of the evaluated methods were built on previously published approaches. One method incorporated a new approach to improve the robustness to image variability.

RESULTS

The new method showed the strongest agreement with the expert. At 20× resolution, it reproduced steatosis area fractions with a mean absolute error of 0.011 for absent or mild steatosis and 0.036 for moderate or severe steatosis. At 10× resolution, it was more accurate than and twice as fast as all other methods at 20× resolution. When compared with SPC performed by two additional human observers, its error was substantially lower than one and only slightly above the other observer.

CONCLUSIONS

The results suggest that the new method can be a suitable automated replacement for SPC. Before further improvements can be verified, it is necessary to thoroughly assess the variability of SPC between human observers.

Endogenous Stem Cells Were Recruited by Defocused Low-Energy Shock Wave in Treating Diabetic Bladder Dysfunction

Defocused low-energy shock wave (DLSW) has been shown effects on activating mesenchymal stromal cells (MSCs) in vitro. In this study, recruitment of endogenous stem cells was firstly examined as an important pathway during the healing process of diabetic bladder dysfunction (DBD) treated by DLSW in vivo. Neonatal rats received intraperitoneal injection of 5-ethynyl-2-deoxyuridine (EdU) and then DBD rat model was created by injecting streptozotocin. Four weeks later, DLSW treatment was performed. Afterward, their tissues were examined by histology. Meanwhile, adipose tissue-derived stem cells (ADSCs) were treated by DLSW in vitro. Results showed DLSW ameliorated voiding function of diabetic rats by recruiting EdU⁺Stro-1⁺CD34^- endogenous stem cells to release abundant nerve growth factor (NGF) and vascular endothelial growth factor (VEGF). Some EdU⁺ cells overlapped with staining of smooth muscle actin. After DLSW treatment, ADSCs showed higher migration ability, higher expression level of stromal cell-derived factor-1 and secreted more NGF and VEGF. In conclusion, DLSW could ameliorate DBD by recruiting endogenous stem cells. Beneficial effects were mediated by secreting NGF and VEGF, resulting into improved innervation and vascularization in bladder.

Clinical Applications of Whole-slide Imaging in Anatomic Pathology

The development of whole-slide imaging has paved the way for digitizing of glass slides that are the basis for surgical pathology. This transformative technology has changed the landscape in research applications and education but despite its tremendous potential, its adoption for clinical use has been slow. We review the various niche applications that initiated awareness of this technology, provide examples of clinical use cases, and discuss the requirements and challenges for full adoption in clinical diagnosis. The opportunities for applications of image analysis tools in a workflow will be changed by integration of whole-slide imaging into routine diagnosis.

The Impact of New Technologic and Molecular Advances in the Daily Practice of Gastrointestinal and Hepatobiliary Pathology

The practice of anatomic pathology, and of gastrointestinal pathology in particular, has been dramatically transformed in the past decade. In addition to the multitude of diseases, syndromes, and clinical entities encountered in daily clinical practice, the increasing integration of new technologic and molecular advances into the field of gastroenterology is occurring at a fast pace. Application of these advances has challenged pathologists to correlate newer methodologies with existing morphologic criteria, which in many instances still provide the gold standard for diagnosis. This review describes the impact of new technologic and molecular advances on the daily practice of gastrointestinal and hepatobiliary pathology. We discuss new drugs that can affect the gastrointestinal tract and liver, new endoluminal techniques, new molecular tests that are often performed reflexively, new imaging techniques for evaluating hepatocellular carcinoma, and modified approaches to the gross and histologic assessment of tissues that have been exposed to neoadjuvant therapies.

Whole Slide Imaging for Analytical Anatomic Pathology and Telepathology: Practical Applications Today, Promises, and Perils

Whole slide imaging (WSI) offers a convenient, tractable platform for measuring features of routine and special-stain histology or in immunohistochemistry staining by using digital image analysis (IA). We now routinely use IA for quantitative and qualitative analysis of theranostic markers such as human epidermal growth factor 2 (HER2/neu), estrogen and progesterone receptors, and Ki-67. Quantitative IA requires extensive validation, however, and may not always be the best approach, with pancreatic neuroendocrine tumors being one example in which a semiautomated approach may be preferable for patient care. We find that IA has great utility for objective assessment of gastrointestinal tract dysplasia, microvessel density in hepatocellular carcinoma, hepatic fibrosis and steatosis, renal fibrosis, and general quality analysis/quality control, although the applications of these to daily practice are still in development. Collaborations with bioinformatics specialists have explored novel applications to gliomas, including in silico approaches for mining histologic data and correlating with molecular and radiologic findings. We and many others are using WSI for rapid, remote-access slide reviews (telepathology), though technical factors currently limit its utility for routine, high-volume diagnostics. In our experience, the greatest current practical impact of WSI lies in facilitating long-term storage and retrieval of images while obviating the need to keep slides on site. Once the existing barriers of capital cost, validation, operator training, software design, and storage/back-up concerns are overcome, these technologies appear destined to be a cornerstone of precision medicine and personalized patient care, and to become a routine part of pathology practice.

NASPGHAN Clinical Practice Guideline for the Diagnosis and Treatment of Nonalcoholic Fatty Liver Disease in Children: Recommendations from the Expert Committee on NAFLD (ECON) and the North American Society of Pediatric Gastroenterology, Hepatology and Nutrition (NASPGHAN)

Nonalcoholic fatty liver disease (NAFLD) is a highly prevalent chronic liver disease that occurs in the setting of insulin resistance and increased adiposity. It has rapidly evolved into the most common liver disease seen in the pediatric population and is a management challenge for general pediatric practitioners, subspecialists, and for health systems. In this guideline, the expert committee on NAFLD reviewed and summarized the available literature, formulating recommendations to guide screening and clinical care of children with NAFLD.

Stereological Analysis of Liver Biopsy Histology Sections as a Reference Standard for Validating Non-Invasive Liver Fat Fraction Measurements by MRI

Background and Aims

Validation of non-invasive methods of liver fat quantification requires a reference standard. However, using standard histopathology assessment of liver biopsies is problematical because of poor repeatability. We aimed to assess a stereological method of measuring volumetric liver fat fraction (VLFF) in liver biopsies and to use the method to validate a magnetic resonance imaging method for measurement of VLFF.

Methods

VLFFs were measured in 59 subjects (1) by three independent analysts using a stereological point counting technique combined with the Delesse principle on liver biopsy histological sections and (2) by three independent analysts using the HepaFat-Scan^® technique on magnetic resonance images of the liver. Bland Altman statistics and intraclass correlation (IC) were used to assess the repeatability of each method and the bias between the methods of liver fat fraction measurement.

Results

Inter-analyst repeatability coefficients for the stereology and HepaFat-Scan^® methods were 8.2 (95% CI 7.7–8.8)% and 2.4 (95% CI 2.2–2.5)% VLFF respectively. IC coefficients were 0.86 (95% CI 0.69–0.93) and 0.990 (95% CI 0.985–0.994) respectively. Small biases (≤3.4%) were observable between two pairs of analysts using stereology while no significant biases were observable between any of the three pairs of analysts using HepaFat-Scan^®. A bias of 1.4±0.5% VLFF was observed between the HepaFat-Scan^® method and the stereological method.

Conclusions

Repeatability of the stereological method is superior to the previously reported performance of assessment of hepatic steatosis by histopathologists and is a suitable reference standard for validating non-invasive methods of measurement of VLFF.

Commentary

Historically, pathologists perform manual evaluation of H&E- or immunohistochemically-stained slides, which can be subjective, inconsistent, and, at best, semiquantitative. As the complexity of staining and demand for increased precision of manual evaluation increase, the pathologist’s assessment will include automated analyses (i.e., “digital pathology”) to increase the accuracy, efficiency, and speed of diagnosis and hypothesis testing and as an important biomedical research and diagnostic tool. This commentary introduces the many roles for pathologists in designing and conducting high-throughput digital image analysis. Pathology review is central to the entire course of a digital pathology study, including experimental design, sample quality verification, specimen annotation, analytical algorithm development, and report preparation. The pathologist performs these roles by reviewing work undertaken by technicians and scientists with training and expertise in image analysis instruments and software. These roles require regular, face-to-face interactions between team members and the lead pathologist. Traditional pathology training is suitable preparation for entry-level participation on image analysis teams. The future of pathology is very exciting, with the expanding utilization of digital image analysis set to expand pathology roles in research and drug development with increasing and new career opportunities for pathologists.

Amino Acid Metabolism is Altered in Adolescents with Nonalcoholic Fatty Liver Disease-An Untargeted, High Resolution Metabolomics Study

OBJECTIVE

To conduct an untargeted, high resolution exploration of metabolic pathways that was altered in association with hepatic steatosis in adolescents.

STUDY DESIGN

This prospective, case-control study included 39 Hispanic-American, obese adolescents aged 11-17 years evaluated for hepatic steatosis using magnetic resonance spectroscopy. Of these 39 individuals, 30 had hepatic steatosis ≥5% and 9 were matched controls with hepatic steatosis <5%. Fasting plasma samples were analyzed in triplicate using ultra-high resolution metabolomics on a Thermo Fisher Q Exactive mass spectrometry system, coupled with C18 reverse phase liquid chromatography. Differences in plasma metabolites between adolescents with and without nonalcoholic fatty liver disease (NAFLD) were determined by independent t tests and visualized using Manhattan plots. Untargeted pathway analyses using Mummichog were performed among the significant metabolites to identify pathways that were most dysregulated in NAFLD.

RESULTS

The metabolomics analysis yielded 9583 metabolites, and 7711 with 80% presence across all samples remained for statistical testing. Of these, 478 metabolites were associated with the presence of NAFLD compared with the matched controls. Pathway analysis revealed that along with lipid metabolism, several major amino acid pathways were dysregulated in NAFLD, with tyrosine metabolism being the most affected.

CONCLUSIONS

Metabolic pathways of several amino acids are significantly disturbed in adolescents with elevated hepatic steatosis. This is a novel finding and suggests that these pathways may be integral in the mechanisms of NAFLD.

Pathological characterization and morphometric analysis of hepatic lesions in SHRSP5/Dmcr, an experimental non-alcoholic steatohepatitis model, induced by high-fat and high-cholesterol diet

SHRSP5/Dmcr is a newly established substrain of stroke-prone spontaneously hypertensive rat (SHRSP). Recently, high-fat and high-cholesterol (HFC) diet-fed SHRSP5/Dmcr has been reported as a novel rat model of developing hepatic lesions similar to human non-alcoholic steatohepatitis (NASH). The aim of this study was to investigate the detailed pathological conditions induced by HFC diet in SHRSP5/Dmcr rats using molecular biological methods and morphometric analysis. SHRSP5/Dmcr rats at 6 weeks of age were fed on either HFC diet or stroke-prone (SP) diet for 2, 4, 6, 8 and 16 weeks and histopathological changes in the liver, blood chemistry and mRNA expression levels in the liver were investigated. As evidenced by the histopathological examination of the liver of the SHRSP5/Dmcr rats, hepatic steatosis and lobular inflammation were present, with gradual increasing severity from 2 weeks after the introduction of the HFC diet. Partial hepatic fibrosis was detected at 6 weeks and spread over the entire region of the liver with more severe bridging formation by 16 weeks. The degrees of NASH-like hepatic lesions such as steatosis (the size distribution of lipid droplets), inflammation and fibrosis were quantified by morphometric analysis. Eosinophilic inclusion bodies encountered in the hepatocytes had immunoreactivity with Cox-4 and double-membrane walls, identified as mega-mitochondria. Serum ALT and bilirubins, and the mRNA expression levels related to fibrosis were closely correlated with hepatic histopathological changes. The clear feeding time-dependent progression of NASH-like hepatic lesion in HFC diet-fed SHRSP5/Dmcr rats reinforced the conclusion that this strain might be a useful model of NASH and of inflammatory fibrotic liver disease.

Chronic Alcohol Consumption Causes Liver Injury in High-Fructose-Fed Male Mice Through Enhanced Hepatic Inflammatory Response

BACKGROUND

Obesity and the metabolic syndrome occur in approximately one-third of patients with alcoholic liver disease (ALD). The increased consumption of fructose parallels the increased prevalence of obesity and the metabolic syndrome in the United States and worldwide. In this study, we investigated whether dietary high fructose potentiates chronic alcohol-induced liver injury, and explored potential mechanism(s).

METHODS

Six-week-old male C57BL/6J mice were assigned to 4 groups: control, high fructose, chronic ethanol (EtOH), and high fructose plus chronic alcohol. The mice were fed either control diet or high-fructose diet (60%, w/w) for 18 weeks. Chronic alcohol-fed mice were given 20% (v/v) ethanol (Meadows-Cook model) ad libitum as the only available liquid from the 9th week through the 18th week. Liver injury, steatosis, hepatic inflammatory gene expression, and copper status were assessed.

RESULTS

High-fructose diet and chronic alcohol consumption alone each induce hepatic fat accumulation and impair copper status. However, the combination of dietary high fructose plus chronic alcohol synergistically induced liver injury as evidenced by robustly increased plasma alanine aminotransferase and aspartate aminotransferase, but the combination did not exacerbate hepatic fat accumulation nor worsen copper status. Moreover, FE-fed mice were characterized by prominent microvesicular steatosis. High-fructose diet and chronic alcohol ingestion together led to a significant up-regulation of Kupffer cell (KC) M1 phenotype gene expression (e.g., tumor necrosis factor-α and monocyte chemoattractant protein-1), as well as Toll-like receptor 4 (TLR4) signaling gene expression, which is also associated with the up-regulation of KCs and activation marker gene expression, including Emr1, CD68, and CD163.

CONCLUSIONS

Our data suggest that dietary high fructose may potentiate chronic alcohol consumption-induced liver injury. The underlying mechanism might be due to the synergistic effect of dietary high fructose and alcohol on the activation of the TLR4 signaling pathway, which in turn leads to KC activation and phenotype switch toward M1 polarization. This study suggests that alcohol-fructose combination contributes to ALD progression.

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.

Normal range of hepatic fat fraction on dual- and triple-echo fat quantification MR in children

Objectives

To evaluate hepatic fat fraction on dual- and triple-echo gradient-recalled echo MRI sequences in healthy children.

Materials and Methods

We retrospectively reviewed the records of children in a medical check-up clinic from May 2012 to November 2013. We excluded children with abnormal laboratory findings or those who were overweight. Hepatic fat fraction was measured on dual- and triple-echo sequences using 3T MRI. We compared fat fractions using the Wilcoxon signed rank test and the Bland-Altman 95% limits of agreement. The correlation between fat fractions and clinical and laboratory findings was evaluated using Spearman’s correlation test, and the cut-off values of fat fractions for diagnosing fatty liver were obtained from reference intervals.

Results

In 54 children (M:F = 26:28; 5–15 years; mean 9 years), the dual fat fraction (0.1–8.0%; median 1.6%) was not different from the triple fat fraction (0.4–6.5%; median 2.7%) (p = 0.010). The dual- and triple-echo fat fractions showed good agreement using a Bland-Altman plot (-0.6 ± 2.8%). Eight children (14.8%) on dual-echo sequences and six (11.1%) on triple-echo sequences had greater than 5% fat fraction. From these children, six out of eight children on dual-echo sequences and four out of six children on triple-echo sequences had a 5–6% hepatic fat fraction. When using a cut-off value of a 6% fat fraction derived from a reference interval, only 3.7% of children were diagnosed with fatty liver. There was no significant correlation between clinical and laboratory findings with dual and triple-echo fat fractions.

Conclusions

Dual fat fraction was not different from triple fat fraction. We suggest a cut-off value of a 6% fat fraction is more appropriate for diagnosing fatty liver on both dual- and triple-echo sequences in children.

Histopathological aspects of liver under variable food restriction: has the intense one-week food restriction a protective effect on non-alcoholic-fatty-liver-disease (NAFLD) development?

Non-alcoholic-fatty-liver-disease (NAFLD) is a clinicopathologic entity characterized by a variety of hepatic injury patterns without significant alcohol use. It has a close association with obesity, so treatment includes weight loss, control of insulin sensitivity, interventions directed at inflammation and fibrosis. There is a certain relationship between the grade and duration of food restriction and hepatic function. The objective of this work was to describe the relationship between biochemistry, autoantibodies, insulin-like growth factor I (IGF-I), insulin-like growth factor binding protein 3 (IGFBP-3), and liver morphology in experimental rabbit groups with food restriction as compared to controls with ad libitum food (ADL) income. The experiment was performed on a total of 24 rabbits of a weaning age of 25-81 days. The first group (R1) was restricted between 32 and 39 days of age to 50 g of food per rabbit a day. The second group (R2) was also restricted between 32 and 39 days, but the rabbits received 65 g of food per rabbit a day. At the end of the experiment, the blood and liver samples were collected at necropsy. NAFLD has developed in all three groups. There was any autoantibody positivity in all three groups. IGF-I is moderately higher in R1 and R2 group, as compared to the control group (P > 0.05). IGFBP-3 is without statistical significance in all three groups. Alkaline phosphatase (ALP) is the only liver biochemical parameter that has significantly increased following food restriction (P > 0.039). Single one-week restriction has any protective effect on NAFLD development.

Reliability of frozen section in the assessment of allograft steatosis in liver transplantation

BACKGROUND

Because liver allograft steatosis is an important risk factor of graft dysfunction after liver transplantation, it must be taken into consideration during graft acceptance. The aim of this study was to evaluate the reliability of frozen section in the assessment of liver steatosis before transplantation.

METHODS

The retrospective analysis was based on data of 112 liver allograft procurements performed between 2003 and 2012. Hepatic steatosis was assessed in frozen and routine sections. Sensitivity, specificity, and positive and negative predictive values of the frozen section were evaluated with respect to detection of >30% and >50% steatosis.

RESULTS

According to routine section assessment, there were 32 (28.6%) cases of steatosis >30% and 16 (14.3%) of >50%. The results of frozen section assessment were underestimated and overestimated in a similar low number of cases, both for the >30% (0.0% and 0.9%, respectively, P < 1.000) and the >50% (4.5% and 0.9%, respectively, P = .221) cutoff. Sensitivity, specificity, positive and negative predictive values of frozen section assessment were 100.0%, 98.8%, 97.0%, and 100.0%, respectively, for detection of >30% steatosis, and 68.8%, 99.0%, 91.7%, and 95.0%, respectively, for >50% steatosis.

CONCLUSIONS

Considering high positive predictive value of frozen section assessment in detection of >50% steatosis, it may serve as a base to discard the use of graft for transplantation. However, according to the relatively moderate sensitivity of this method, decision of graft acceptance must also be made on consideration of other well-known factors for poor posttransplant function.

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.