Evolution of the liver biopsy and its future

Role of the angiopoietin-like protein family in the progression of NAFLD

Non-alcoholic fatty liver disease (NAFLD) is the most frequent cause of chronic liver disease, with a range of conditions including non-alcoholic fatty liver, non-alcoholic steatohepatitis, cirrhosis, and hepatocellular carcinoma (HCC). Currently recognized as the liver component of the metabolic syndrome, NAFLD is intimately linked to metabolic diseases. Angiopoietin-like proteins (ANGPTLs) comprise a class of proteins that resemble angiopoietins structurally. It is closely related to obesity, insulin resistance and lipid metabolism, and may be the critical factor of metabolic syndrome. In recent years, many studies have found that there is a certain correlation between ANGPTLs and the occurrence and progression of NAFLD disease spectrum. This article reviews the possible mechanisms and roles of ANGPTL protein in the pathogenesis and progression of NAFLD.

Mistakes in utilising histopathology for the management of liver disease

INTRODUCTION

Liver biopsy has become selective due to its invasiveness, potential adverse effects, patient acceptance and cost. Furthermore, the emergence of noninvasive tests (NITs) has challenged the necessity of liver biopsies in specific clinical situations. However, liver biopsy continues to play a crucial role in disease diagnosis, prognosis, and evaluating treatment compliance and response in selected patients.

AREAS COVERED

In this narrative review, we discuss the errors and the shortcomings that can occur at various stages, from the initial patient selection for a liver biopsy to the final reporting phase, and strategies to address them. Clinicians and pathologists must take all necessary precautions to mitigate potential shortcomings that could compromise the value of liver biopsies.

EXPERT OPINION

The increasing sophistication of NITs offers a safer, more convenient, and potentially more cost-effective approach to diagnosing chronic liver disease, especially for assessing the degree of liver fibrosis. As NITs continue to evolve, liver biopsy will likely transition to a more targeted role, ensuring optimal patient care in the ever-changing field of hepatology. However, liver biopsy will continue to have a pivotal role in assessing acute liver disease where the diagnostic yield of the liver biopsy still outweighs that of NITs.

The Use of Artificial Intelligence in the Liver Histopathology Field: A Systematic Review

Digital pathology (DP) has begun to play a key role in the evaluation of liver specimens. Recent studies have shown that a workflow that combines DP and artificial intelligence (AI) applied to histopathology has potential value in supporting the diagnosis, treatment evaluation, and prognosis prediction of liver diseases. Here, we provide a systematic review of the use of this workflow in the field of hepatology. Based on the PRISMA 2020 criteria, a search of the PubMed, SCOPUS, and Embase electronic databases was conducted, applying inclusion/exclusion filters. The articles were evaluated by two independent reviewers, who extracted the specifications and objectives of each study, the AI tools used, and the results obtained. From the 266 initial records identified, 25 eligible studies were selected, mainly conducted on human liver tissues. Most of the studies were performed using whole-slide imaging systems for imaging acquisition and applying different machine learning and deep learning methods for image pre-processing, segmentation, feature extractions, and classification. Of note, most of the studies selected demonstrated good performance as classifiers of liver histological images compared to pathologist annotations. Promising results to date bode well for the not-too-distant inclusion of these techniques in clinical practice.

Digital pathology systems enabling quality patient care

Pathology laboratories are undergoing digital transformations, adopting innovative technologies to enhance patient care. Digital pathology systems impact clinical, education, and research use cases where pathologists use digital technologies to perform tasks in lieu of using glass slides and a microscope. Pathology professional societies have established clinical validation guidelines, and the US Food and Drug Administration have also authorized digital pathology systems for primary diagnosis, including image analysis and machine learning systems. Whole slide images, or digital slides, can be viewed and navigated similar to glass slides on a microscope. These modern tools not only enable pathologists to practice their routine clinical activities, but can potentially enable digital computational discovery. Assimilation of whole slide images in pathology clinical workflow can further empower machine learning systems to support computer assisted diagnostics. The potential enrichment these systems can provide is unprecedented in the field of pathology. With appropriate integration, these clinical decision support systems will allow pathologists to increase the delivery of quality patient care. This review describes the digital pathology transformation process, applicable clinical use cases, incorporation of image analysis and machine learning systems in the clinical workflow, as well as future technologies that may further disrupt pathology modalities to deliver quality patient care.

From NAFLD to HCC: Advances in noninvasive diagnosis

Non-alcoholic fatty liver disease (NAFLD) has gradually become one of the major liver health problems in the world. The dynamic course of the disease goes through steatosis, inflammation, fibrosis, and carcinoma. Before progressing to carcinoma, timely and effective intervention will make the condition better, which highlights the importance of early diagnosis. With the further study of the biological mechanism in the pathogenesis and progression of NAFLD, some potential biomarkers have been discovered, and the possibility of their clinical application is gradually being discussed. At the same time, the progress of imaging technology and the emergence of new materials and methods also provide more possibilities for the diagnosis of NAFLD. This article reviews the diagnostic markers and advanced diagnostic methods of NAFLD in recent years.

HIGH-DENSITY LIPOPROTEIN CHOLESTEROL AND SYSTEMIC ARTERIAL HYPERTENSION ARE ASSOCIATED WITH HEPATIC NECROINFLAMMATORY ACTIVITY IN PATIENTS WITH CHRONIC HEPATITIS C

•HDL cholesterol levels <60 mg/dL were independently associated with necroinflammatory activity in chronic hepatitis C (CHC). •CHC patients with hypertension are at an increased risk of developing necroinflammatory activity. •In patients with CHC, liver fibrosis was independently associated with old age, steatosis, and HDL-C <60 mg/dL. •Triglycerides levels ≥150 mg/dL were associated with lobular inflammatory activity in patients with CHC. Background - Approximately 71 million people are chronically infected with hepatitis C virus (HCV) worldwide. A significant number of these individuals will develop liver cirrhosis and/or hepatocellular carcinoma. Beyond the liver, there is a sizeable body of scientific evidence linking cardiovascular disease and chronic hepatitis C (CHC); however, the biological mechanisms behind the concurrence of these conditions have not been completely clarified yet. Objective - To evaluate associations between hepatic histology, clinical comorbidities and lipid profile in patients with CHC. To investigate associations between liver histology and demographic, nutritional, biochemical and virological parameters. Methods - Eight-five patients with CHC prospectively underwent hepatic biopsy. Liver fragments were obtained from each patient by percutaneous route using a Menghini needle. Fibrosis was evaluated according to the METAVIR scoring system, as follows: F0, no fibrosis; F1, fibrous portal expansion; F2, fibrous portal widening with few septa; F3, bridging fibrosis with architectural distortion; and F4, liver cirrhosis. The activity was classified based on the degree of lymphocyte infiltration and hepatocyte necrosis, from A0 to A3. The diagnosis of liver disease was based on clinical, biochemical, histological, and radiological methods. The data were analyzed by logistic regression models. Results - This cross-sectional study included 85 outpatients followed at the tertiary care ambulatory centre with a mean age of 57.2±10.7 years and 45 (52.9%) were females. There were 10 patients with cirrhosis. Patients with a METAVIR F3-F4 were significantly older (P=0.02) and had higher levels of ALT (P=0.0006), AST (P<0.0001), γ-GT (P=0.03) and bilirubin (P=0.001) and higher prothrombin time than patients with F0-F2 score. Albumin levels (P=0.01) were significantly lower in METAVIR F3-F4. Age (OR=1.09; 95%CI=1.02-1.16; P=0.02), steatosis (OR=4.03; 95%CI=1.05-15.45; P=0.04) and high-density lipoprotein cholesterol (HDL-C) <60 mg/dL (OR=7.67; 95%CI=1.71-34.49; P=0.008) were independently associated with fibrosis. Hypertension (OR=6.36; 95%CI=1.31-30.85; P=0.02) and HDL-C <60 mg/dL (OR=9.85; 95%CI=2.35-41.39; P=0.002) were independently associated with necroinflammatory activity. Hypertension (OR=6.94; 95%CI=1.92-25.05; P=0.003) and HDL-C <60 mg/dL (OR=3.94; 95%CI=1.27-12.3; P=0.02) were associated with interface inflammatory activity. Triglycerides (TG ≥150 mg/dL) remained associated with lobular inflammatory activity. Conclusion - cholesterol levels <60 mg/dL were independently associated with necroinflammatory activity in chronic hepatitis C. Patients with hypertension are at an increased risk of developing necroinflammatory activity.

Spatial Omics Imaging of Fresh-Frozen Tissue and Routine FFPE Histopathology of a Single Cancer Needle Core Biopsy: A Freezing Device and Multimodal Workflow

The complex molecular alterations that underlie cancer pathophysiology are studied in depth with omics methods using bulk tissue extracts. For spatially resolved tissue diagnostics using needle biopsy cores, however, histopathological analysis using stained FFPE tissue and the immunohistochemistry (IHC) of a few marker proteins is currently the main clinical focus. Today, spatial omics imaging using MSI or IRI is an emerging diagnostic technology for the identification and classification of various cancer types. However, to conserve tissue-specific metabolomic states, fast, reliable, and precise methods for the preparation of fresh-frozen (FF) tissue sections are crucial. Such methods are often incompatible with clinical practice, since spatial metabolomics and the routine histopathology of needle biopsies currently require two biopsies for FF and FFPE sampling, respectively. Therefore, we developed a device and corresponding laboratory and computational workflows for the multimodal spatial omics analysis of fresh-frozen, longitudinally sectioned needle biopsies to accompany standard FFPE histopathology of the same biopsy core. As a proof-of-concept, we analyzed surgical human liver cancer specimens using IRI and MSI with precise co-registration and, following FFPE processing, by sequential clinical pathology analysis of the same biopsy core. This workflow allowed for a spatial comparison between different spectral profiles and alterations in tissue histology, as well as a direct comparison for histological diagnosis without the need for an extra biopsy.

Deep-Learning-Based Hepatic Ploidy Quantification Using H&E Histopathology Images

Polyploidy, the duplication of the entire genome within a single cell, is a significant characteristic of cells in many tissues, including the liver. The quantification of hepatic ploidy typically relies on flow cytometry and immunofluorescence (IF) imaging, which are not widely available in clinical settings due to high financial and time costs. To improve accessibility for clinical samples, we developed a computational algorithm to quantify hepatic ploidy using hematoxylin-eosin (H&E) histopathology images, which are commonly obtained during routine clinical practice. Our algorithm uses a deep learning model to first segment and classify different types of cell nuclei in H&E images. It then determines cellular ploidy based on the relative distance between identified hepatocyte nuclei and determines nuclear ploidy using a fitted Gaussian mixture model. The algorithm can establish the total number of hepatocytes and their detailed ploidy information in a region of interest (ROI) on H&E images. This is the first successful attempt to automate ploidy analysis on H&E images. Our algorithm is expected to serve as an important tool for studying the role of polyploidy in human liver disease.

Multimodal NASH prognosis using 3D imaging flow cytometry and artificial intelligence to characterize liver cells

To improve the understanding of the complex biological process underlying the development of non-alcoholic steatohepatitis (NASH), 3D imaging flow cytometry (3D-IFC) with transmission and side-scattered images were used to characterize hepatic stellate cell (HSC) and liver endothelial cell (LEC) morphology at single-cell resolution. In this study, HSC and LEC were obtained from biopsy-proven NASH subjects with early-stage NASH (F2-F3) and healthy controls. Here, we applied single-cell imaging and 3D digital reconstructions of healthy and diseased cells to analyze a spatially resolved set of morphometric cellular and texture parameters that showed regression with disease progression. By developing a customized autoencoder convolutional neural network (CNN) based on label-free cell transmission and side scattering images obtained from a 3D imaging flow cytometer, we demonstrated key regulated cell types involved in the development of NASH and cell classification performance superior to conventional machine learning methods.

A Framework for Augmented Intelligence in Allergy and Immunology Practice and Research—A Work Group Report of the AAAAI Health Informatics, Technology, and Education Committee

Artificial and augmented intelligence (AI) and machine learning (ML) methods are expanding into the health care space. Big data are increasingly used in patient care applications, diagnostics, and treatment decisions in allergy and immunology. How these technologies will be evaluated, approved, and assessed for their impact is an important consideration for researchers and practitioners alike. With the potential of ML, deep learning, natural language processing, and other assistive methods to redefine health care usage, a scaffold for the impact of AI technology on research and patient care in allergy and immunology is needed. An American Academy of Asthma Allergy and Immunology Health Information Technology and Education subcommittee workgroup was convened to perform a scoping review of AI within health care as well as the specialty of allergy and immunology to address impacts on allergy and immunology practice and research as well as potential challenges including education, AI governance, ethical and equity considerations, and potential opportunities for the specialty. There are numerous potential clinical applications of AI in allergy and immunology that range from disease diagnosis to multidimensional data reduction in electronic health records or immunologic datasets. For appropriate application and interpretation of AI, specialists should be involved in the design, validation, and implementation of AI in allergy and immunology. Challenges include incorporation of data science and bioinformatics into training of future allergists-immunologists.

Ex Vivo Fluorescence Confocal Microscopy in Specimens of the Liver: A Proof-of-Concept Study

Ex vivo Fluorescence Confocal Microscopy (FCM) is a technique providing high-resolution images of native tissues. The method is increasingly used in surgical settings in areas of dermatology and urology. Only a few publications exist about examinations of tumors and non-neoplastic lesions of the liver. We report on the application of FCM in biopsies, surgical specimens and autopsy material (33 patients, 39 specimens) of the liver and compare the results to conventional histology. Our preliminary examinations indicated a perfect suitability for tumor diagnosis (ĸ = 1.00) and moderate/good suitability for the assessment of inflammation (ĸ = 0.4-0.6) with regard to their severity and localization. Macro-vesicular steatosis was reliably detected, micro-vesicular steatosis tended to be underestimated. Cholestasis and eosinophilic granules in granulocytes were not represented in the scans. The tissue was preserved as native material and maintained its quality for downstream histological, immunohistological and molecular examinations. In summary, FCM is a material sparing method that provides rapid feedback to the clinician about the presence of tumor, the degree of inflammation and structural changes. This can lead to faster therapeutic decisions in the management of liver tumors, treatment of hepatitis or in liver transplant medicine.

Nonalcoholic Fatty Liver Disease (NAFLD): Pathogenesis and Noninvasive Diagnosis

The global prevalence of nonalcoholic fatty liver disease (NAFLD) or metabolic associated fatty liver disease (MAFLD), as it is now known, has gradually increased. NAFLD is a disease with a spectrum of stages ranging from simple fatty liver (steatosis) to a severe form of steatosis, nonalcoholic steatohepatitis (NASH), which could progress to irreversible liver injury (fibrosis) and organ failure, and in some cases hepatocellular carcinoma (HCC). Although a liver biopsy remains the gold standard for accurate detection of this condition, it is unsuitable for clinical screening due to a higher risk of death. There is thus an increased need to find alternative techniques or tools for accurate diagnosis. Early detection for NASH matters for patients because NASH is the marker for severe disease progression. This review summarizes the current noninvasive tools for NAFLD diagnosis and their performance. We also discussed potential and newer alternative tools for diagnosing NAFLD.

The Need for Alternatives to Liver Biopsies: Non-Invasive Analytics and Diagnostics

Histology remains essential for the diagnosis and management of many disorders affecting the liver. However, the biopsy procedure itself is associated with a low risk of harm to the patient and cost to the health services; samples may not be adequate and are subject to sampling variation. Furthermore, interpretation often depends on the skill of the pathologist. Increasingly, new techniques are becoming available that are altering the indications for liver biopsy. Many diseases of the liver can be diagnosed and managed using serological and radiological techniques; the degree of fibrosis and fat can often be assessed by serological or imaging techniques and the nature of space occupying lesions defined by serology, imaging and use of liquid biopsy. However, these techniques, too, are subject to limitations: sensitivity and specificity is not always adequate for diagnosis or management; some techniques are expensive and often also require expert interpretation. Although there may be less need for liver biopsy today, histology remains the gold standard as well as an essential tool for the diagnosis and management of many conditions, especially where there are multiple pathologies, or where a diagnosis cannot or has not been made by alternative approaches. Until less invasive techniques become more reliable and accessible, liver histology will remain a key investigation.