Digital liver biopsy: Bio-imaging of fatty liver for translational and clinical research

Renal Perfusion, Oxygenation and Metabolism: The Role of Imaging

Thanks to technical advances in the field of medical imaging, it is now possible to study key features of renal anatomy and physiology, but so far poorly explored due to the inherent difficulties in studying both the metabolism and vasculature of the human kidney. In this narrative review, we provide an overview of recent research findings on renal perfusion, oxygenation, and substrate uptake. Most studies evaluating renal perfusion with positron emission tomography (PET) have been performed in healthy controls, and specific target populations like obese individuals or patients with renovascular disease and chronic kidney disease (CKD) have rarely been assessed. Functional magnetic resonance (fMRI) has also been used to study renal perfusion in CKD patients, and recent studies have addressed the kidney hemodynamic effects of therapeutic agents such as glucagon-like receptor agonists (GLP-1RA) and sodium-glucose co-transporter 2 inhibitors (SGLT2-i) in an attempt to characterise the mechanisms leading to their nephroprotective effects. The few available studies on renal substrate uptake are discussed. In the near future, these imaging modalities will hopefully become widely available with researchers more acquainted with them, gaining insights into the complex renal pathophysiology in acute and chronic diseases.

Taurine Protects against the Fatty Liver Hemorrhagic Syndrome in Laying Hens through the Regulation of Mitochondrial Homeostasis

Metabolic-associated fatty liver disease (MAFLD) is a chronic liver disease caused by fat deposition in the liver of humans and mammals, while fatty liver hemorrhagic syndrome (FLHS) is a fatty liver disease in laying hens which can increase the mortality and cause severe economic losses to the laying industry. Increasing evidence has shown a close relationship between the occurrence of fatty liver disease and the disruption of mitochondrial homeostasis. Studies have proven that taurine can regulate hepatic fat metabolism, reduce hepatic fatty deposition, inhibit oxidative stress, and alleviate mitochondrial dysfunction. However, the mechanisms by which taurine regulates mitochondrial homeostasis in hepatocytes need to be further studied. In this study, we determined the effects and mechanisms of taurine on high-energy low-protein diet-induced FLHS in laying hens and in cultured hepatocytes in free fatty acid (FFA)-induced steatosis. The liver function, lipid metabolism, antioxidant capacity, mitochondrial function, mitochondrial dynamics, autophagy, and biosynthesis were detected. The results showed impaired liver structure and function, mitochondrial damage and dysfunction, lipid accumulation, and imbalance between mitochondrial fusion and fission, mitochondrial autophagy, and biosynthesis in both FLHS hens and steatosis hepatocytes. Taurine administration can significantly inhibit the occurrence of FLHS, protect mitochondria in hepatocytes from disease induced by lipid accumulation and FFA, up-regulate the expression levels of Mfn1, Mfn2, Opa1, LC3I, LC3II, PINK1, PGC-1α, Nrf1, Nrf2, and Tfam, and down-regulate the expression levels of Fis1, Drp1, and p62. In conclusion, taurine can protect laying hens from FLHS through the regulation of mitochondrial homeostasis, including the regulation of mitochondrial dynamics, autophagy, and biosynthesis.

Renal toxicity and biokinetics models after repeated uranium instillation

During nuclear fuel processing, workers can potentially be exposed to repeated inhalations of uranium compounds. Uranium nephrotoxicity is well documented after acute uranium intake, but it is controversial after long-term or protracted exposure. This study aims to analyze the nephrotoxicity threshold after repeated uranium exposure through upper airways and to investigate the resulting uranium biokinetics in comparison to reference models. Mice (C57BL/6J) were exposed to uranyl nitrate (0.03-3 mg/kg/day) via intranasal instillation four times a week for two weeks. Concentrations of uranium in urines and tissues were measured at regular time points (from day 1 to 91 post-exposure). At each exposure level, the amount of uranium retained in organs/tissues (kidney, lung, bone, nasal compartment, carcass) and excreta (urine, feces) reflected the two consecutive weeks of instillation except for renal uranium retention for the highest uranium dose. Nephrotoxicity biomarkers, KIM-1, clusterin and osteopontin, are induced from day 4 to day 21 and associated with changes in renal function (arterial fluxes) measured using non-invasive functional imaging (Doppler-ultrasonography) and confirmed by renal histopathological analysis. These results suggest that specific biokinetic models should be developed to consider altered uranium excretion and retention in kidney due to nephrotoxicity. The threshold is between 0.25 and 1 mg/kg/day after repeated exposure to uranium via upper airways.

Role of pan immune inflammatory value in the evaluation of hepatosteatosis in children and adolescents with obesity

OBJECTIVES

Inflammation is a feature of non-alcoholic fatty liver disease progression and plays an important role in hepatic steatosis and fibrosis. Since there are no studies in the literature showing the relationship between hepatosteatosis with the systemic immune-inflammation index (SII) and pan-immune inflammation value (PIV), we aimed to evaluate the relationship between these biomarkers and hepatosteatosis in childhood.

METHODS

We included 133 consecutive obese children and adolescents aged 6-18 years into this single-center, retrospective, and cross-sectional study. Anthropometric, physical examination, radiological and laboratory data were obtained and recorded from the file records of each case.

RESULTS

When we grouped the patient population according to the grade of hepatosteatosis, there was a statistically significant difference between the groups in terms of SII and PIV values (p<0.05, for both). In the analyzes performed to identify independent predictors of hepatosteatosis pubertal status (p=0.019) and PIV value (p<0.001) were found to be significant as independent predictors. Moreover, in the analysis performed to predict severity of hepatic steatosis, regression analysis was performed by dividing the groups into groups with and without severe adiposity. As a result of this analysis, HOMA-IR (p=0.019) and PIV value (p=0.028) were found to be significant in the prediction of severe hepatic adiposity.

CONCLUSIONS

Our findings showed that increased PIV levels were associated with the presence and severity of hepatic steatosis, but not with SII.

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.

The application of artificial intelligence in hepatology: A systematic review

The integration of human and artificial intelligence (AI) in medicine has only recently begun but it has already become obvious that intelligent systems can dramatically improve the management of liver diseases. Big data made it possible to envisage transformative developments of the use of AI for diagnosing, predicting prognosis and treating liver diseases, but there is still a lot of work to do. If we want to achieve the 21^st century digital revolution, there is an urgent need for specific national and international rules, and to adhere to bioethical parameters when collecting data. Avoiding misleading results is essential for the effective use of AI. A crucial question is whether it is possible to sustain, technically and morally, the process of integration between man and machine. We present a systematic review on the applications of AI to hepatology, highlighting the current challenges and crucial issues related to the use of such technologies.

Application of artificial intelligence in liver diseases: From diagnosis to treatment

Infectious or noninfectious liver disease has inexorably risen as one of the leading causes of global death and disease burden. There were an estimated 2.14 million liver-related deaths in 2017, representing an 11.4% increase since 2012. Traditional diagnosis and treatment methods have various dilemmas in different causes of liver disease. As a hot research topic in recent years, the application of artificial intelligence (AI) in different fields has attracted extensive attention, and new technologies have brought more ideas for the diagnosis and treatment of some liver diseases. Machine learning (ML) is the core of AI and the basic way to make a computer intelligent. ML technology has many potential uses in hepatology, ranging from exploring new noninvasive means to predict or diagnose different liver diseases to automated image analysis. The application of ML in liver diseases can help clinical staff to diagnose and treat different liver diseases quickly, accurately and scientifically, which is of importance for reducing the incidence and mortality of liver diseases, reducing medical errors, and promoting the development of medicine. This paper reviews the application and prospects of AI in liver diseases, and aims to improve clinicians’ awareness of the importance of AI in the diagnosis and treatment of liver diseases.

A deep look into radiomics

Radiomics is a process that allows the extraction and analysis of quantitative data from medical images. It is an evolving field of research with many potential applications in medical imaging. The purpose of this review is to offer a deep look into radiomics, from the basis, deeply discussed from a technical point of view, through the main applications, to the challenges that have to be addressed to translate this process in clinical practice. A detailed description of the main techniques used in the various steps of radiomics workflow, which includes image acquisition, reconstruction, pre-processing, segmentation, features extraction and analysis, is here proposed, as well as an overview of the main promising results achieved in various applications, focusing on the limitations and possible solutions for clinical implementation. Only an in-depth and comprehensive description of current methods and applications can suggest the potential power of radiomics in fostering precision medicine and thus the care of patients, especially in cancer detection, diagnosis, prognosis and treatment evaluation.

Brain-gut-liver interactions across the spectrum of insulin resistance in metabolic fatty liver disease

Metabolic associated fatty liver disease (MAFLD), formerly named "nonalcoholic fatty liver disease" occurs in about one-third of the general population of developed countries worldwide and behaves as a major morbidity and mortality risk factor for major causes of death, such as cardiovascular, digestive, metabolic, neoplastic and neuro-degenerative diseases. However, progression of MAFLD and its associated systemic complications occur almost invariably in patients who experience the additional burden of intrahepatic and/or systemic inflammation, which acts as disease accelerator. Our review is focused on the new knowledge about the brain-gut-liver axis in the context of metabolic dysregulations associated with fatty liver, where insulin resistance has been assumed to play an important role. Special emphasis has been given to digital imaging studies and in particular to positron emission tomography, as it represents a unique opportunity for the noninvasive in vivo study of tissue metabolism. An exhaustive revision of targeted animal models is also provided in order to clarify what the available preclinical evidence suggests for the causal interactions between fatty liver, dysregulated endogenous glucose production and insulin resistance.

Comparison of Multimaterial Decomposition Fat Fraction with DECT and Proton Density Fat Fraction with IDEAL IQ MRI for Quantification of Liver Steatosis in a Population Exposed to Chemotherapy

Introduction:

Oncologic patients who develop chemotherapy-associated liver injury (CALI) secondary to chemotherapy treatment tend to have worse outcomes. Biopsy remains the gold standard for the diagnosis of hepatic steatosis. The purpose of this article is to compare 2 alternatives: Proton-Density-Fat-Fraction (PDFF) MRI and MultiMaterial-Decomposition (MMD) DECT.

Materials and Methods:

49 consecutive oncologic patients treated with Chemotherapy underwent abdominal DECT and abdominal MRI within 2 weeks of each other. Two radiologists tracked Regions of Interest independently both in the PDFF fat maps and in the MMD DECT fat maps. Non-parametric exact Wilcoxon signed rank test and Cohen’s K were used to compare the 2 sequences and to evaluate the agreement.

Results:

There was no statistically significant difference in the fat fraction measured as a continuous value between PDFF and DECT between 2 readers. Within the same imaging method (PDFF) the degree of agreement based on the k coefficient between reader 1 and reader 2 is 0.88 (p-value < 0.05). Similarly, for single-source DECT(ssDECT) the degree of agreement based on the k coefficient between reader 1 and reader 2 is 0.97 (p-value < 0.05).

Conclusions:

The results of this study demonstrate that the hepatic fat fraction of ssDECT with MMD are not significantly different from PDFF. This could be an advantage in an oncological population that undergoes serial CT scans for follow up of chemotherapy response.

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.

The Discovery of Endoplasmic Reticulum Storage Disease. The Connection between an H&E Slide and the Brain

The revolutionary evolution in science and technology over the last few decades has made it possible to face more adequately three main challenges of modern medicine: changes in old diseases, the appearance of new diseases, and diseases that are unknown (mostly genetic), despite research efforts. In this paper we review the road travelled by pathologists in search of a method based upon the use of routine instruments and techniques which once were available for research only. The application to tissue studies of techniques from immunology, molecular biology, and genetics has allowed dynamic interpretations of biological phenomena with special regard to gene regulation and expression. That implies stepwise investigations, including light microscopy, immunohistochemistry, in situ hybridization, electron microscopy, molecular histopathology, protein crystallography, and gene sequencing, in order to progress from suggestive features detectable in routinely stained preparations to more characteristic, specific, and finally, pathognomonic features. Hematoxylin and Eosin (H&E)-stained preparations and appropriate immunohistochemical stains have enabled the recognition of phenotypic changes which may reflect genotypic alterations. That has been the case with hepatocytic inclusions detected in H&E-stained preparations, which appeared to correspond to secretory proteins that, due to genetic mutations, were retained within the rough endoplasmic reticulum (RER) and were deficient in plasma. The identification of this phenomenon affecting the molecules alpha-1-antitrypsin and fibrinogen has led to the discovery of a new field of cell organelle pathology, endoplasmic reticulum storage disease(s) (ERSD). Over fifty years, pathologists have wandered through a dark forest of complicated molecules with strange conformations, and by detailed observations in simple histopathological sections, accompanied by a growing background of molecular techniques and revelations, have been able to recognize and identify arrays of grotesque polypeptide arrangements.

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.

Hepatic fat as clinical outcome and therapeutic target for nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is rapidly becoming the leading cause of advanced liver disease in Western countries. NAFLD is defined in the presence of increased hepatic fat content, which is mainly stored under the form of neutral lipids within intracellular droplets and is not explained by at risk alcohol intake. In order to understand the pathogenesis, monitor the progression and find novel treatments for this condition, previous research efforts mainly addressed the role of inflammation. However, very recent data seem to suggest that hepatic lipid accumulation may be involved in NAFLD pathogenesis by driving secondary inflammation and fibrosis progression. Here, we will briefly review the novel results derived from natural history, genetics, imaging studies and therapeutic trials that support the notion that hepatic fat accumulation may represent a major clinical outcome and therapeutic target for NAFLD. Indeed, prospective and genetic data are consistent with hepatic fat being a driver of NAFLD progression. Furthermore, new technologies will render possible to monitor hepatic fat content without the need of invasive assessment, thereby allowing to identify patients at higher risk, and to monitor the response to drugs that act by decreasing hepatic lipid accumulation.

Pediatric Fatty Liver and Obesity: Not Always Justa Matter of Non-Alcoholic Fatty Liver Disease

Obesity-related non-alcoholic fatty liver disease (NAFLD) represents the most common cause of pediatric liver disease due to overweight/obesity large-scale epidemics. In clinical practice, diagnosis is usually based on clinical features, blood tests, and liver imaging. Here, we underline the need to make a correct differential diagnosis for a number of genetic, metabolic, gastrointestinal, nutritional, endocrine, muscular, and systemic disorders, and for iatrogenic/viral/autoimmune hepatitis as well. This is all the more important for patients who are not in the NAFLD classical age range and for those for whom a satisfactory response of liver test abnormalities to weight loss after dietary counseling and physical activity measures cannot be obtained or verified due to poor compliance. A correct diagnosis may be life-saving, as some of these conditions which appear similar to NAFLD have a specific therapy. In this study, the characteristics of the main conditions which require consideration are summarized, and a practical diagnostic algorithm is discussed.