Inter-observer and Intra-observer Agreement in Pathological Evaluation of Non-alcoholic Fatty Liver Disease Suspected Liver Biopsies

Artificial intelligence scoring of liver biopsies in a phase II trial of semaglutide in nonalcoholic steatohepatitis

BACKGROUND AND AIMS

Artificial intelligence-powered digital pathology offers the potential to quantify histological findings in a reproducible way. This analysis compares the evaluation of histological features of NASH between pathologists and a machine-learning (ML) pathology model.

APPROACH AND RESULTS

This post hoc analysis included data from a subset of patients (n=251) with biopsy-confirmed NASH and fibrosis stage F1-F3 from a 72-week randomized placebo-controlled trial of once-daily subcutaneous semaglutide 0.1, 0.2, or 0.4 mg (NCT02970942). Biopsies at baseline and week 72 were read by 2 pathologists. Digitized biopsy slides were evaluated by PathAI's NASH ML models to quantify changes in fibrosis, steatosis, inflammation, and hepatocyte ballooning using categorical assessments and continuous scores. Pathologist and ML-derived categorical assessments detected a significantly greater percentage of patients achieving the primary endpoint of NASH resolution without worsening of fibrosis with semaglutide 0.4 mg versus placebo (pathologist 58.5% vs. 22.0%, p < 0.0001; ML 36.9% vs. 11.9%; p =0.0015). Both methods detected a higher but nonsignificant percentage of patients on semaglutide 0.4 mg versus placebo achieving the secondary endpoint of liver fibrosis improvement without NASH worsening. ML continuous scores detected significant treatment-induced responses in histological features, including a quantitative reduction in fibrosis with semaglutide 0.4 mg versus placebo ( p =0.0099) that could not be detected using pathologist or ML categorical assessment.

CONCLUSIONS

ML categorical assessments reproduced pathologists' results of histological improvement with semaglutide for steatosis and disease activity. ML-based continuous scores demonstrated an antifibrotic effect not measured by conventional histopathology.

Precision diagnostics in transplanted organs using microarray-assessed gene expression: concepts and technical methods of the Molecular Microscope® Diagnostic System (MMDx)

There is a major unmet need for improved accuracy and precision in the assessment of transplant rejection and tissue injury. Diagnoses relying on histologic and visual assessments demonstrate significant variation between expert observers (as represented by low kappa values) and have limited ability to assess many biological processes that produce little histologic changes, for example, acute injury. Consensus rules and guidelines for histologic diagnosis are useful but may have errors. Risks of over- or under-treatment can be serious: many therapies for transplant rejection or primary diseases are expensive and carry risk for significant adverse effects. Improved diagnostic methods could alleviate healthcare costs by reducing treatment errors, increase treatment efficacy, and serve as useful endpoints for clinical trials of new agents that can improve outcomes. Molecular diagnostic assessments using microarrays combined with machine learning algorithms for interpretation have shown promise for increasing diagnostic precision via probabilistic assessments, recalibrating standard of care diagnostic methods, clarifying ambiguous cases, and identifying potentially missed cases of rejection. This review describes the development and application of the Molecular Microscope® Diagnostic System (MMDx), and discusses the history and reasoning behind many common methods, statistical practices, and computational decisions employed to ensure that MMDx scores are as accurate and precise as possible. MMDx provides insights on disease processes and highly reproducible results from a comparatively small amount of tissue and constitutes a general approach that is useful in many areas of medicine, including kidney, heart, lung, and liver transplants, with the possibility of extrapolating lessons for understanding native organ disease states.

Liver histology is associated with long-term clinical outcomes in patients with metabolic dysfunction-associated steatohepatitis

BACKGROUND

Few studies have examined the risk of long-term clinical outcomes in patients with metabolic dysfunction-associated steatohepatitis in relation to liver histology. We aimed to study this using a real-world cohort.

METHODS

Adults (N = 702) recorded on Vanderbilt University Medical Center's Synthetic Derivative database (1984-2021) with evidence of metabolic dysfunction-associated steatohepatitis on liver biopsy were followed from the first biopsy until the first clinical event or last database entry (median: 4.7 y). Risks of cirrhosis (N = 650), other noncirrhotic liver-related (N = 702) and cardiovascular-related outcomes (N = 660), and mortality due to liver, cardiovascular, or cancer events (N = 660) were determined as a function of baseline histology (fibrosis stage [F], lobular inflammation grade [LI], hepatocyte ballooning grade [HB], and steatosis score) adjusting for sex, age, diabetes, and weight-loss surgery.

RESULTS

Cirrhosis risk was reduced for lower versus higher fibrosis stage (HR: F0-1 vs. F3: 0.22 [95% CI: 0.12-0.42]), LI1 versus LI2-3 (0.42 [0.19-0.97]), and HB1 versus HB2 (0.20 [0.08-0.50]). Lower fibrosis stage was associated with significantly lower risks of liver-related outcomes versus F4 cirrhosis (eg, F0-1: 0.12 [0.05-0.25]), whereas no differences were seen across baseline lobular inflammation, hepatocyte ballooning, and steatosis grades/scores. Lower versus higher lobular inflammation grade was associated with lower risks for liver-related outcomes in patients with weight-loss surgery. There was a trend for lower risks for cardiovascular-related and any long-term outcomes with lower versus higher fibrosis stage.

CONCLUSIONS

Fibrosis stage and lobular inflammation and hepatocyte ballooning grades predict the risk of long-term outcomes, supporting the use of these histological features as potential surrogate markers of disease progression or clinical outcomes.

This Is What Metabolic Dysfunction-Associated Steatotic Liver Disease Looks Like: Potential of a Multiparametric MRI Protocol

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent condition with a broad spectrum defined by liver biopsy. This gold standard method evaluates three features: steatosis, activity (ballooning and lobular inflammation), and fibrosis, attributing them to certain grades or stages using a semiquantitative scoring system. However, liver biopsy is subject to numerous restrictions, creating an unmet need for a reliable and reproducible method for MASLD assessment, grading, and staging. Noninvasive imaging modalities, such as magnetic resonance imaging (MRI), offer the potential to assess quantitative liver parameters. This review aims to provide an overview of the available MRI techniques for the three criteria evaluated individually by liver histology. Here, we discuss the possibility of combining multiple MRI parameters to replace liver biopsy with a holistic, multiparametric MRI protocol. In conclusion, the development and implementation of such an approach could significantly improve the diagnosis and management of MASLD, reducing the need for invasive procedures and paving the way for more personalized treatment strategies.

Head-to-head comparison of magnetic resonance elastography-based liver stiffness, fat fraction, and T1 relaxation time in identifying at-risk NASH

BACKGROUND AND AIMS

The presence of at-risk NASH is associated with an increased risk of cirrhosis and complications. Therefore, noninvasive identification of at-risk NASH with an accurate biomarker is a critical need for pharmacologic therapy. We aim to explore the performance of several magnetic resonance (MR)-based imaging parameters in diagnosing at-risk NASH.

APPROACH AND RESULTS

This prospective clinical trial (NCT02565446) includes 104 paired MR examinations and liver biopsies performed in patients with suspected or diagnosed NAFLD. Magnetic resonance elastography-assessed liver stiffness (LS), 6-point Dixon-derived proton density fat fraction (PDFF), and single-point saturation-recovery acquisition-calculated T1 relaxation time were explored. Among all predictors, LS showed the significantly highest accuracy in diagnosing at-risk NASH [AUC LS : 0.89 (0.82, 0.95), AUC PDFF : 0.70 (0.58, 0.81), AUC T1 : 0.72 (0.61, 0.82), z -score test z >1.96 for LS vs any of others]. The optimal cutoff value of LS to identify at-risk NASH patients was 3.3 kPa (sensitivity: 79%, specificity: 82%, negative predictive value: 91%), whereas the optimal cutoff value of T1 was 850 ms (sensitivity: 75%, specificity: 63%, and negative predictive value: 87%). PDFF had the highest performance in diagnosing NASH with any fibrosis stage [AUC PDFF : 0.82 (0.72, 0.91), AUC LS : 0.73 (0.63, 0.84), AUC T1 : 0.72 (0.61, 0.83), |z| <1.96 for all].

CONCLUSION

Magnetic resonance elastography-assessed LS alone outperformed PDFF, and T1 in identifying patients with at-risk NASH for therapeutic trials.

[State of the art on the pathophysiology, diagnosis and treatment of non-alcoholic steatohepatitis (NASH)]

NAFLD or non-alcoholic fatty liver disease is one of the complications of obesity and diabetes, the prevalence of which is increasing. The causes of the pathology and its development towards its severe form, NASH or non-alcoholic steatohepatitis, are multiple and still poorly understood. Many different pharmacological classes are being tested in clinical trials to treat NASH, but no pharmaceutical treatment is currently on the market. Moreover, the diagnosis of certainty is only possible by liver biopsy and histological analysis, an invasive procedure with high risk for the patient. It is therefore necessary to better understand the natural history of the disease in order to identify therapeutic targets, but also to identify markers for the diagnosis and monitoring of the disease using a blood sample, which will allow an improvement in patient management.

Artificial intelligence and deep learning: new tools for histopathological diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis

Nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH) is associated with metabolic syndrome and is rapidly increasing globally with the increased prevalence of obesity. Although noninvasive diagnosis of NAFLD/NASH has progressed, pathological evaluation of liver biopsy specimens remains the gold standard for diagnosing NAFLD/NASH. However, the pathological diagnosis of NAFLD/NASH relies on the subjective judgment of the pathologist, resulting in non-negligible interobserver variations. Artificial intelligence (AI) is an emerging tool in pathology to assist diagnoses with high objectivity and accuracy. An increasing number of studies have reported the usefulness of AI in the pathological diagnosis of NAFLD/NASH, and our group has already used it in animal experiments. In this minireview, we first outline the histopathological characteristics of NAFLD/NASH and the basics of AI. Subsequently, we introduce previous research on AI-based pathological diagnosis of NAFLD/NASH.

Histological assessment based on liver biopsy: the value and challenges in NASH drug development

Nonalcoholic steatohepatitis (NASH) is increasingly recognized as a serious disease that can lead to cirrhosis, hepatocellular carcinoma (HCC), and death. However, there is no effective drug to thwart the progression of the disease. Development of new drugs for NASH is an urgent clinical need. Liver biopsy plays a key role in the development of new NASH drugs. Histological findings based on liver biopsy are currently used as the main inclusion criteria and the primary therapeutic endpoint in NASH clinical trials. However, there are inherent challenges in the use of liver biopsy in clinical trials, such as evaluation reliability, sampling error, and invasive nature of the procedure. In this article, we review the advantages and value of liver histopathology based on liver biopsy in clinical trials of new NASH drugs. We also discuss the challenges and limitations of liver biopsy and identify future drug development directions.

Development and validation of a non-invasive model for diagnosing HBV-related liver cirrhosis

BACKGROUND

Liver cirrhosis is closely related to the abnormal liver function and occurrence of liver cancer. Accurate non-invasive assessment of liver cirrhosis is of great significance for preventing disease progression and treatment decision-making. We aim to develop and validate a non-invasive diagnostic model for liver cirrhosis in patients with chronic hepatitis B (CHB).

METHODS

From July 2015 to April 2017, seven-hundred fifty-four patients with primary HBV-related liver cancer who underwent hepatectomy were reprospectively recruited. All patients were examined with 2D-SWE and serologic testing preoperatively, which were utilized for measurement of liver stiffness and serum fibrosis models. The stage of liver fibrosis was evaluated using a resected liver specimen. Least absolute shrinkage and selection operator (Lasso) regression was used for feature selection and binary logistic regression analysis was chosen to build a diagnostic model, which was presented as a nomogram and evaluated for calibration, discrimination and clinical usefulness. The performance of noninvasive model was then prospectively validated in an independent cohort (361 patients) by the ROC curve analysis.

RESULTS

The diagnostic model, which consists of 5 selected clinical characteristics (PIII-NP, IV-C, Hyaluronan, Platelet and Liver stiffness), showed the strongest correlation with liver fibrosis stage (ρ = 0.702, P < 0.05). Compared with APRI, FIB-4, King's Score, and Forns Index, the model presented the optimal discrimination and the best predictive performance with the highest AUC in the training cohort (0.866, 95%CI 0.840-0.892, P < 0.05) and validation cohorts (0.852, 95%CI 0.813-0.890, P < 0.05). Decision curve analysis demonstrated that nomogram based on the model was extremely useful for diagnosing cirrhosis in patients with chronic hepatitis B.

CONCLUSION

This study proposes a non-invasive diagnostic model that incorporates the clinical predictors which can be conveniently used in the individualized diagnosis of HBV-related liver cirrhosis.

Determination of Non-Invasive Biomarkers for the Assessment of Fibrosis, Steatosis and Hepatic Iron Overload by MR Image Analysis. A Pilot Study

The reference diagnostic test of fibrosis, steatosis, and hepatic iron overload is liver biopsy, a clear invasive procedure. The main objective of this work was to propose HSA, or human serum albumin, as a biomarker for the assessment of fibrosis and to study non-invasive biomarkers for the assessment of steatosis and hepatic iron overload by means of an MR image acquisition protocol. It was performed on a set of eight subjects to determine fibrosis, steatosis, and hepatic iron overload with four different MRI sequences. We calibrated longitudinal relaxation times (T1 [ms]) with seven human serum albumin (HSA [%]) phantoms, and we studied the relationship between them as this protein is synthesized by the liver, and its concentration decreases in advanced fibrosis. Steatosis was calculated by means of the fat fraction (FF [%]) between fat and water liver signals in “fat-only images” (the subtraction of in-phase [IP] images and out-of-phase [OOP] images) and in “water-only images” (the addition of IP and OOP images). Liver iron concentration (LIC [µmol/g]) was obtained by the transverse relaxation time (T2* [ms]) using Gandon’s method with multiple echo times (TE) in T2-weighted IP and OOP images. The preliminary results showed that there is an inverse relationship (r = −0.9662) between the T1 relaxation times (ms) and HSA concentrations (%). Steatosis was determined with FF > 6.4% and when the liver signal was greater than the paravertebral muscles signal, and thus, the liver appeared hyperintense in fat-only images. Hepatic iron overload was detected with LIC > 36 µmol/g, and in these cases, the liver signal was smaller than the paravertebral muscles signal, and thus, the liver behaved as hypointense in IP images.

A large-scale internal validation study of unsupervised virtual trichrome staining technologies on nonalcoholic steatohepatitis liver biopsies

Non-alcoholic steatohepatitis (NASH) is a fatty liver disease characterized by accumulation of fat in hepatocytes with concurrent inflammation and is associated with morbidity, cirrhosis and liver failure. After extraction of a liver core biopsy, tissue sections are stained with hematoxylin and eosin (H&E) to grade NASH activity, and stained with trichrome to stage fibrosis. Methods to computationally transform one stain into another on digital whole slide images (WSI) can lessen the need for additional physical staining besides H&E, reducing personnel, equipment, and time costs. Generative adversarial networks (GAN) have shown promise for virtual staining of tissue. We conducted a large-scale validation study of the viability of GANs for H&E to trichrome conversion on WSI (n = 574). Pathologists were largely unable to distinguish real images from virtual/synthetic images given a set of twelve Turing Tests. We report high correlation between staging of real and virtual stains ([Formula: see text]; 95% CI: 0.84-0.88). Stages assigned to both virtual and real stains correlated similarly with a number of clinical biomarkers and progression to End Stage Liver Disease (Hazard Ratio HR = 2.06, 95% CI: 1.36-3.12, p < 0.001 for real stains; HR = 2.02, 95% CI: 1.40-2.92, p < 0.001 for virtual stains). Our results demonstrate that virtual trichrome technologies may offer a software solution that can be employed in the clinical setting as a diagnostic decision aid.

Quantitative multiparametric magnetic resonance imaging can aid non-alcoholic steatohepatitis diagnosis in a Japanese cohort

BACKGROUND

Non-invasive assessment of non-alcoholic steatohepatitis (NASH) is increasing in desirability due to the invasive nature and costs associated with the current form of assessment; liver biopsy. Quantitative multiparametric magnetic resonance imaging (mpMRI) to measure liver fat (proton density fat fraction) and fibroinflammatory disease [iron-corrected T1 (cT1)], as well as elastography techniques [vibration-controlled transient elastography (VCTE) liver stiffness measure], magnetic resonance elastography (MRE) and 2D Shear-Wave elastography (SWE) to measure stiffness and fat (controlled attenuated parameter, CAP) are emerging alternatives which could be utilised as safe surrogates to liver biopsy.

AIM

To evaluate the agreement of non-invasive imaging modalities with liver biopsy, and their subsequent diagnostic accuracy for identifying NASH patients.

METHODS

From January 2019 to February 2020, Japanese patients suspected of NASH were recruited onto a prospective, observational study and were screened using non-invasive imaging techniques; mpMRI with LiverMultiScan^®, VCTE, MRE and 2D-SWE. Patients were subsequently biopsied, and samples were scored by three independent pathologists. The diagnostic performances of the non-invasive imaging modalities were assessed using area under receiver operating characteristic curve (AUC) with the median of the histology scores as the gold standard diagnoses. Concordance between all three independent pathologists was further explored using Krippendorff’s alpha (a) from weighted kappa statistics.

RESULTS

N = 145 patients with mean age of 60 (SD: 13 years.), 39% females, and 40% with body mass index ≥ 30 kg/m² were included in the analysis. For identifying patients with NASH, MR liver fat and cT1 were the strongest performing individual measures (AUC: 0.80 and 0.75 respectively), and the mpMRI metrics combined (cT1 and MR liver fat) were the overall best non-invasive test (AUC: 0.83). For identifying fibrosis ≥ 1, MRE performed best (AUC: 0.97), compared to VCTE-liver stiffness measure (AUC: 0.94) and 2D-SWE (AUC: 0.94). For assessment of steatosis ≥ 1, MR liver fat was the best performing non-invasive test (AUC: 0.92), compared to controlled attenuated parameter (AUC: 0.75). Assessment of the agreement between pathologists showed that concordance was best for steatosis (a = 0.58), moderate for ballooning (a = 0.40) and fibrosis (a = 0.40), and worst for lobular inflammation (a = 0.11).

CONCLUSION

Quantitative mpMRI is an effective alternative to liver biopsy for diagnosing NASH and non-alcoholic fatty liver, and thus may offer clinical utility in patient management.

Identification of tissue sections from decellularized liver scaffolds for repopulation experiments

BACKGROUND

Biological organ engineering is a novel experimental approach to generate functional liver grafts by decellularization and repopulation. Currently, healthy organs of small or large animals and human organs with preexisting liver diseases are used to optimize decellularization and repopulation.However, the effects of morphological changes on allo- and xenogeneic cell-scaffold interactions during repopulation procedure, e.g., using scaffold-sections, are unknown. We present a sequential morphological workflow to identify murine liver scaffold-sections with well-preserved microarchitecture.

METHODS

Native livers (CONT, n = 9) and livers with experimentally induced pathologies (hepatics steatosis: STEA, n = 7; hepatic fibrosis induced by bile duct ligation: BDL, n = 9; nodular regenerative hyperplasia induced by 90% partial hepatectomy: PH, n = 8) were decellularized using SDS and Triton X-100 to generate cell-free scaffolds. Scaffold-sections were assessed using a sequential morphological workflow consisting of macroscopic, microscopic and morphological evaluation: (1) The scaffold was evaluated by a macroscopic decellularization score. (2) Regions without visible tissue remnants were localized for sampling and histological processing. Subsequent microscopical examination served to identify tissue samples without cell remnants. (3) Only cell-free tissue sections were subjected to detailed liver-specific morphological assessment using a histological and immunohistochemical decellularization score.

RESULTS

Decellularization was feasible in 33 livers, which were subjected to the sequential morphological workflow. In 11 of 33 scaffolds we achieved a good macroscopic decellularization result (CONT: 3 scaffolds; STEA: 3 scaffolds; BDL: 3 scaffolds; PH: 2 scaffolds). The microscopic assessment resulted in the selection of 88 cell-free tissue sections (CONT: 15 sections; STEA: 38 sections; BDL: 30 sections; PH: 5 sections). In 27 of those sections we obtained a good histological decellularization result (CONT: 3 sections; STEA: 6 sections; BDL: 17 sections; PH: 1 section). All experimental groups contained sections with a good immunohistochemical decellularization result (CONT: 6 sections; STEA: 5 sections; BDL: 4 sections; PH: 1 section).

DISCUSSION

Decellularization was possible in all experimental groups, irrespectively of the underlying morphological alteration. Furthermore, our proposed sequential morphological workflow was suitable to detect tissue sections with well-preserved hepatic microarchitecture, as needed for further repopulation experiments.

Assessment of hepatic steatosis by controlled attenuation parameter using the M and XL probes: an individual patient data meta-analysis

BACKGROUND

Diagnostic tools for liver disease can now include estimation of the grade of hepatic steatosis (S0 to S3). Controlled attenuation parameter (CAP) is a non-invasive method for assessing hepatic steatosis that has become available for patients who are obese (FibroScan XL probe), but a consensus has not yet been reached regarding cutoffs and its diagnostic performance. We aimed to assess diagnostic properties and identify relevant covariates with use of an individual patient data meta-analysis.

METHODS

We did an individual patient data meta-analysis, in which we searched PubMed and Web of Science for studies published from database inception until April 30, 2019. Studies reporting original biopsy-controlled data of CAP for non-invasive grading of steatosis were eligible. Probe recommendation was based on automated selection, manual assessment of skin-to-liver-capsule distance, and a body-mass index (BMI) criterion. Receiver operating characteristic methods and mixed models were used to assess diagnostic properties and covariates. Patients with non-alcoholic fatty liver disease (NAFLD) were analysed separately because they are the predominant patient group when using the XL probe. This study is registered with PROSPERO, CRD42018099284.

FINDINGS

16 studies reported histology-controlled CAP including the XL probe, and individual data from 13 papers and 2346 patients were included. Patients with a mean age of 46·5 years (SD 14·5) were recruited from 20 centres in nine countries. 2283 patients had data for BMI; 673 (29%) were normal weight (BMI <25 kg/m²), 530 (23%) were overweight (BMI ≥25 to <30 kg/m²), and 1080 (47%) were obese (BMI ≥30 kg/m²). 1277 (54%) patients had NAFLD, 474 (20%) had viral hepatitis, 285 (12%) had alcohol-associated liver disease, and 310 (13%) had other liver disease aetiologies. The XL probe was recommended in 1050 patients, 930 (89%) of whom had NAFLD; among the patients with NAFLD, the areas under the curve were 0·819 (95% CI 0·769-0·869) for S0 versus S1 to S3 and 0·754 (0·720-0·787) for S0 to S1 versus S2 to S3. CAP values were independently affected by aetiology, diabetes, BMI, aspartate aminotransferase, and sex. Optimal cutoffs differed substantially across aetiologies. Risk of bias according to QUADAS-2 was low.

INTERPRETATION

CAP cutoffs varied according to cause, and can effectively recognise significant steatosis in patients with viral hepatitis. CAP cannot grade steatosis in patients with NAFLD adequately, but its value in a NAFLD screening setting needs to be studied, ideally with methods beyond the traditional histological reference standard.

FUNDING

The German Federal Ministry of Education and Research and Echosens.

Combined methods of optical spectroscopy and artificial intelligence in the assessment of experimentally induced non-alcoholic fatty liver

BACKGROUND AND OBJECTIVE

Due to the existing prevalence of nonalcoholic fatty liver disease (NAFLD) and its relation to the epidemic of obesity in the general population, it is imperative to develop detection and evaluation methods of the early stages of the disease with improved efficacy over the current diagnostic approaches. We aimed to obtain an improved diagnosis, combining methods of optical spectroscopy -diffuse reflectance and fluorescence- with statistical data analysis applied to detect early stages of NAFLD.

METHODS

Statistical analysis scheme based on quadratic discriminant analysis followed by canonical discriminant analysis were applied to the diffuse reflectance data combined with endogenous fluorescence spectral data excited at one of these wavelengths: 330, 365, 385, 405 or 415 nm. The statistical scheme was also applied to the combinations of fluorescence spectrum (405 nm) with each one of the other fluorescence spectra. Details of the developed software, including the application of machine learning algorithms to the combination of spectral data followed by classification statistical schemes, are discussed.

RESULTS

Steatosis progression was differentiated with little classification error (≤1.3%) by using diffuse reflectance and endogenous fluorescence at different wavelengths. Similar results were obtained using fluorescence at 405 nm and one of the other fluorescence spectra (classification error ≤1.0%). Adding the corresponding areas under the curves to the above combinations of spectra diminished errors to 0.6% and 0.3% or less, respectively. The best results for the compounded reflectance-plus-fluorescence spectra were obtained with fluorescence spectra excited at 415 nm with a total classification error of 0.2%; for the combination of the 405nm-excited fluorescence spectrum with another fluorescence spectrum, the best results were achieved for 385 nm, for which total relative classification error amounted 0.4%. The consideration of the area under the spectral curves further improved both classifiers, reducing the error to 0.0% in both cases.

CONCLUSION

Spectrometric techniques combined with statistical processing are a promising tool to improve steatosis classification through a label free approach. However, statistical schemes here applied, might result complex for the everyday medical practice, the designed software including machine learning algorithms is able to render automatic classification of samples according to their steatosis grade with low error.

Suboptimal reliability of liver biopsy evaluation has implications for randomized clinical trials

BACKGROUND & AIMS

Liver biopsies are a critical component of pivotal studies in non-alcoholic steatohepatitis (NASH), constituting inclusion criteria, risk stratification factors and endpoints. We evaluated the reliability of NASH Clinical Research Network scoring of liver biopsies in a NASH clinical trial.

METHODS

Digitized slides of 678 biopsies from 339 patients with paired biopsies randomized into the EMMINENCE study - examining a novel insulin sensitizer (MSDC-0602K) in NASH - were read independently by 3 hepatopathologists blinded to treatment code and scored using the NASH CRN histological scoring system. Various endpoints were computed from these scores.

RESULTS

Inter-reader linearly weighted kappas were 0.609, 0.484, 0.328, and 0.517 for steatosis, fibrosis, lobular inflammation, and ballooning, respectively. Inter-reader unweighted kappas were 0.400 for the diagnosis of NASH, 0.396 for NASH resolution without worsening fibrosis, and 0.366 for fibrosis improvement without worsening NASH. In the current study, 46.3% of the patients included in the study based on 1 hepatopathologist's qualifying reading were deemed not to meet the study's histologic inclusion criteria by at least 1 of the 3 hepatopathologists. The MSDC-0602K treatment effect was lowest for those histologic features with lower inter-reader reliability. Simulations show that the lack of reliability of endpoints and inclusion criteria can drastically reduce study power - from >90% in a well-powered study to as low as 40%.

CONCLUSIONS

The reliability of hepatopathologists' liver biopsy evaluation using currently accepted criteria is suboptimal. This lack of reliability may affect NASH pivotal studies by introducing patients who do not meet NASH study entry criteria, misclassifying fibrosis subgroups, and attenuating apparent treatment effects.

LAY SUMMARY

Since liver biopsy analysis plays such an important role in clinical studies of non-alcoholic steatohepatitis, it is important to understand the reliability of hepato-pathologist readings. We examined both inter- and intra-reader variability in a large data set of paired liver biopsies from a clinical trial. We found very poor inter-reader and modest intra-reader variability. This result has important implications for entry criteria, fibrosis stratification, and the ability to measure a treatment effect in clinical trials.

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

The molecular diagnosis of rejection in liver transplant biopsies: First results of the INTERLIVER study

Molecular diagnosis of rejection is emerging in kidney, heart, and lung transplant biopsies and could offer insights for liver transplant biopsies. We measured gene expression by microarrays in 235 liver transplant biopsies from 10 centers. Unsupervised archetypal analysis based on expression of previously annotated rejection-related transcripts identified 4 groups: normal "R1_normal " (N = 129), T cell-mediated rejection (TCMR) "R2_TCMR " (N = 37), early injury "R3_injury " (N = 61), and fibrosis "R4_late " (N = 8). Groups differed in median time posttransplant, for example, R3_injury 99 days vs R4_late 3117 days. R2_TCMR biopsies expressed typical TCMR-related transcripts, for example, intense IFNG-induced effects. R3_injury displayed increased expression of parenchymal injury transcripts (eg, hypoxia-inducible factor EGLN1). R4_late biopsies showed immunoglobulin transcripts and injury-related transcripts. R2_TCMR correlated with histologic rejection although with many discrepancies, and R4_late with fibrosis. R2_TCMR , R3_injury , and R4_late correlated with liver function abnormalities. Supervised classifiers trained on histologic rejection showed less agreement with histology than unsupervised R2_TCMR scores. No confirmed cases of clinical antibody-mediated rejection (ABMR) were present in the population, and strategies that previously revealed ABMR in kidney and heart transplants failed to reveal a liver ABMR phenotype. In conclusion, molecular analysis of liver transplant biopsies detects rejection, has the potential to resolve ambiguities, and could assist with immunosuppressive management.

A scoring system for the diagnosis of non-alcoholic steatohepatitis from liver biopsy

Background

Liver biopsy is the essential method to diagnose non-alcoholic steatohepatitis (NASH), but histological features of NASH are too subjective to achieve reproducible diagnoses in early stages of disease. We aimed to identify the key histological features of NASH and devise a scoring model for diagnosis.

Methods

Thirteen pathologists blindly assessed 12 histological factors and final histological diagnoses (‘not-NASH,’ ‘borderline,’ and ‘NASH’) of 31 liver biopsies that were diagnosed as non-alcoholic fatty liver disease (NAFLD) or NASH before and after consensus. The main histological parameters to diagnose NASH were selected based on histological diagnoses and the diagnostic accuracy and agreement of 12 scoring models were compared for final diagnosis and the NAFLD Activity Score (NAS) system.

Results

Inter-observer agreement of final diagnosis was fair (κ = 0.25) before consensus and slightly improved after consensus (κ = 0.33). Steatosis at more than 5% was the essential parameter for diagnosis. Major diagnostic factors for diagnosis were fibrosis except 1C grade and presence of ballooned cells. Minor diagnostic factors were lobular inflammation (≥ 2 foci/ × 200 field), microgranuloma, and glycogenated nuclei. All 12 models showed higher inter-observer agreement rates than NAS and post-consensus diagnosis (κ = 0.52–0.69 vs. 0.33). Considering the reproducibility of factors and practicability of the model, summation of the scores of major (× 2) and minor factors may be used for the practical diagnosis of NASH.

Conclusions

A scoring system for the diagnosis of NAFLD would be helpful as guidelines for pathologists and clinicians by improving the reproducibility of histological diagnosis of NAFLD.

Correlations Between MRI Biomarkers PDFF and cT1 With Histopathological Features of Non-Alcoholic Steatohepatitis

INTRODUCTION

Late stage clinical trials in non-alcoholic steatohepatitis (NASH) are currently required by the FDA to use liver biopsy as a primary endpoint. The well-reported limitations with biopsy, such as associated risks and sampling error, coupled with patient preference, are driving investigation into non-invasive alternatives. MRI-derived biomarkers proton density fat fraction (PDFF) and iron-corrected T1 mapping (cT1) are gaining traction as emerging alternatives to biopsy for NASH. Our aim was to explore the correlations between cT1 and PDFF (from LiverMultiScan®), with the histological components on the NAFLD-NASH spectrum in a large cohort of cross-sectional data, in order to calibrate the measurement to histology, and to infer what might constitute a clinically meaningful change when related to the FDA's criteria.

MATERIALS AND METHODS

In a retrospective analysis of data combined from three previously published observational NASH studies, in which adult participants who underwent liver biopsy on suspicion of NAFLD or NASH and had an MRI scan measuring cT1 and PDFF (LiverMultiScan®, Perspectum Ltd, UK), associations between imaging biomarkers and histology were tested using Spearman's rank correlation coefficient (r_s), and further exploration of the relationships between the imaging variables and histology were performed using linear regression.

RESULTS

N = 264 patients with mean age of 54 (SD:9.9), 39% female, and 69% with BMI ≥ 30kg.m^-2 were included in the analysis. cT1 and PDFF both correlated with all features of the NAFLD activity score (NAS). cT1 was also positively correlated with Kleiner-Brunt fibrosis. Partial correlations, adjusting for steatosis, revealed cT1 correlated with inflammation and fibrosis, whereas PDFF did not, and both were still associated with the NAS, but correlation was weaker with PDFF than cT1. An estimated difference of 88 ms in cT1, or 21% relative difference in PDFF was related to a two-point difference in overall NAS.

CONCLUSION

The correlations between cT1 and PDFF with the histopathological hallmarks of NASH demonstrate the potential utility of both cT1 and PDFF as non-invasive biomarkers to detect a pharmacodynamic change in NASH, with cT1 showing superiority for detecting changes in inflammation and fibrosis, rather than liver fat alone.

Deep learning enables pathologist-like scoring of NASH models

Non-alcoholic fatty liver disease (NAFLD) and the progressive form of non-alcoholic steatohepatitis (NASH) are diseases of major importance with a high unmet medical need. Efficacy studies on novel compounds to treat NAFLD/NASH using disease models are frequently evaluated using established histological feature scores on ballooning, inflammation, steatosis and fibrosis. These features are assessed by a trained pathologist using microscopy and assigned discrete scores. We demonstrate how to automate these scores with convolutional neural networks (CNNs). Whole slide images of stained liver sections are analyzed using two different scales with four CNNs, each specialized for one of four histopathological features. A continuous value is obtained to quantify the extent of each feature, which can be used directly to provide a high resolution readout. In addition, the continuous values can be mapped to obtain the established discrete pathologist-like scores. The automated deep learning-based scores show good agreement with the trainer - a human pathologist.

R2 relaxometry based MR imaging for estimation of liver iron content: A comparison between two methods

PURPOSE

To compare the reproducibility and accuracy of R2-relaxometry MRI for estimation of liver iron concentration (LIC) between in-house analysis and FDA-approved commercially available third party results.

METHODS

All MR studies were performed on a 1.5T scanner. Multi-echo spin-echo scans with a fixed TR and increasing TE values of 6 ms, 9 ms, 12 ms, 15 ms, and 18 ms (spaced at 3 ms intervals) were used. Post-processing of the images to calculate mean relaxivity, R2, included drawing of regions of interest to include the whole liver on mid-slice. The relationship between liver R2 values and estimated LIC calculated with in-house analysis and values reported by an external company (FerriScan^®, Resonance Health, Australia) were assessed with correlation coefficients and Bland-Altman difference plots. Continuous variables are presented as mean ± standard deviation. Significance was set at p value < 0.05.

RESULTS

474 studies from 175 patients were included in the study (mean age 10.4 ± 4.2 years (range 1-18 years); 254 studies from girls, 220 studies from boys). LIC ranged from 0.6 to 43 mg/g dry tissue, covering a broad range from normal levels to extremely high iron levels. Linearity between proprietary and in-house methods was excellent across the observed range for R2 (31.5 to 334.8 s^-1); showing a correlation coefficient of r = 0.87, p < 0.001. Bland-Altman R2 difference plot between the two methods shows a mean bias of + 21.5 s^-1 (range - 47.0 to + 90.0 s^-1 between two standard deviations). LIC reported by FerriScan^® compared with LIC estimated in-house with R2 as reported by FerriScan^® agreed strongly, (r = 1.0, p < 0.001).

CONCLUSION

R2 relaxometry MR imaging for liver iron concentration estimation is reproducible between proprietary FDA-approved commercial software and in-house analysis methods.

Study of Methionine Choline Deficient Diet-Induced Steatosis in Mice Using Endogenous Fluorescence Spectroscopy

Non-alcoholic fatty liver disease is a highly prevalent condition worldwide that increases the risk to develop liver fibrosis, cirrhosis, and hepatocellular carcinoma. Thus, it is imperative to develop novel diagnostic tools that together with liver biopsy help to differentiate mild and advanced degrees of steatosis. Ex-vivo liver samples were collected from mice fed a methionine-choline deficient diet for two or eight weeks, and from a control group. The degree of hepatic steatosis was histologically evaluated, and fat content was assessed by Oil-Red O staining. On the other hand, fluorescence spectroscopy was used for the assessment of the steatosis progression. Fluorescence spectra were recorded at excitation wavelengths of 330, 365, 385, 405, and 415 nm by establishing surface contact of the fiber optic probe with the liver specimens. A multi-variate statistical approach based on principal component analysis followed by quadratic discriminant analysis was applied to spectral data to obtain classifiers able to distinguish mild and moderate stages of steatosis at the different excitation wavelengths. Receiver Operating Characteristic (ROC) curves were computed to compare classifier’s performances for each one of the five excitation wavelengths and steatosis stages. Optimal sensitivity and specificity were calculated from the corresponding ROC curves using the Youden index. Intensity in the endogenous fluorescence spectra at the given wavelengths progressively increased according to the time of exposure to diet. The area under the curve of the spectra was able to discriminate control liver samples from those with steatosis and differentiate among the time of exposure to the diet for most of the used excitation wavelengths. High specificities and sensitivities were obtained for every case; however, fluorescence spectra obtained by exciting with 405 nm yielded the best results distinguishing between the mentioned classes with a total classification error of 1.5% and optimal sensitivities and specificities better than 98.6% and 99.3%, respectively.

Inter-observer Variability in Histomorphological Evaluation of Non-neoplastic Liver Biopsy Tissue and Impact of Clinical Information on Final Diagnosis in Shahid Beheshti University of Medical Sciences Affiliated Hospitals

Background & Objective:

Liver biopsy is the main method for grading and staging liver disorders, but the effects of clinical information and optimal biopsy specimen size on interpretation remain contentious. The aim of the study was to evaluate the impact of clinical information and quality of liver specimen on inter-observer agreement for liver disease.

Methods:

A total of 289 consecutive biopsy specimens from 2010 to 2017 were re-evaluated by five pathologists using the modified Ishak and non-alcoholic fatty liver diseases (NAFLD) activity score (NAS) systems. Detailed clinical information was extracted from medical records of patients and the size of all liver biopsy samples was recorded.

Results:

Full agreement between primary diagnosis and final diagnosis was obtained in 214 cases (74%). The remaining cases, namely 22 (7.6%) and 53 (18.3%) biopsies had minor and major diagnostic discrepancies, respectively. The results showed that the overall agreement was significantly higher in cases with complete clinical information than patients without any clinical information and even with partial clinical information (P<0.001). Interestingly, no significant difference in inter-observer agreement was achieved with a length over 20 mm (P=0.181). However, the inter-observer variation significantly decreased when the number of portal tract was more than 10 (P=0.001).

Conclusion:

This study identified the impact of clinical information and the number of portal tracts as the key factors to diagnosis. Therefore, request forms for liver biopsies should always be accompanied with the clinical history. Moreover, adequacy of biopsy specimens is very useful for accurate evaluation of samples by pathologists.

Wisteria floribunda agglutinin-positive mac-2 binding protein as an age-independent fibrosis marker in nonalcoholic fatty liver disease

The assessment of liver fibrosis is essential because it correlates with mortality risk in nonalcoholic fatty liver disease (NAFLD). This study aims to examine whether serum fibrosis markers could identify candidate patients likely to have advanced fibrosis. We enrolled 352 patients with NAFLD and performed liver biopsies in 97 patients. The area under the receiver operating characteristic curve (AUROC) of liver stiffness by magnetic resonance elastography for histological advanced fibrosis was 0.910, and the optimal cutoff value was 4.07 kPa. To predict severe liver stiffness (≥4.07 kPa), the AUROC for Wisteria floribunda agglutinin-positive mac-2 binding protein (WFA+-M2BP) and FIB-4 were 0.897 (cutoff value, 1.08) and 0.880 (cutoff value, 2.53), respectively. After stratification of patients into four age groups as quartile, the optimal cutoff values of WFA+-M2BP for predicting severe liver stiffness were similar in each group (1.09, 1.08, 1.10, and 1.12). On the other hand, those of FIB-4 increased in parallel with age (1.47, 2.19, 2.99, and 3.88). In conclusion, WFA+-M2BP was precise for estimating severe liver stiffness in NAFLD with single cutoff value independent of age. Hence, identifying high-risk cases using WFA+-M2BP from a large number of NAFLD patients is clinically significant.

Prediction of nonalcoholic fatty liver disease (NAFLD) activity score (NAS) with multiparametric hepatic magnetic resonance imaging and elastography

OBJECTIVES

To investigate the use of MR elastography (MRE)-derived mechanical properties (shear stiffness (|G*|) and loss modulus (G″)) and MRI-derived fat fraction (FF) to predict the nonalcoholic fatty liver disease (NAFLD) activity score (NAS) in a NAFLD mouse model.

METHODS

Eighty-nine male mice were studied, including 64 training and 25 independent testing animals. An MRI/MRE exam and histologic evaluation were performed. Pairwise, nonparametric comparisons and multivariate analyses were used to evaluate the relationships between the three imaging parameters (FF, |G*|, and G″) and histologic features. A virtual NAS score (vNAS) was generated by combining three imaging parameters with an ordinal logistic model (OLM) and a generalized linear model (GLM). The prediction accuracy was evaluated by ROC analyses.

RESULTS

The combination of FF, |G*|, and G″ predicted NAS > 1 with excellent accuracy in both training and testing sets (AUROC > 0.84). OLM and GLM predictive models misclassified 3/54 and 6/54 mice in the training, and 1/25 and 1/25 in the testing cohort respectively, in distinguishing between "not-NASH" and "definite-NASH." "Borderline-NASH" prediction was poorer in the training set, and no borderline-NASH mice were available in the testing set.

CONCLUSION

This preliminary study shows that multiparametric MRI/MRE can be used to accurately predict the NAS score in a NAFLD animal model, representing a promising alternative to liver biopsy for assessing NASH severity and treatment response.

KEY POINTS

• MRE-derived liver stiffness and loss modulus and MRI-assessed fat fraction can be used to predict NAFLD activity score (NAS) in our preclinical mouse model (AUROC > 0.84 for all NAS levels greater than 1). • The overall agreement between the histological-determined NASH diagnosis and the imaging-predicted NASH diagnosis is 80-92%. • The multiparametric hepatic MRI/MRE has great potential for noninvasively assessing liver disease severity and treatment efficacy.

Magnetic resonance elastography SE-EPI vs GRE sequences at 3T in a pediatric population with liver disease

PURPOSE

The goal of our study is to compare hepatic stiffness measures using gradient-recalled echo (GRE) versus spin-echo echo planar imaging (SE-EPI)-based MR Elastography (MRE) at 3T used to measure hepatic stiffness in a patients with suspected liver diseases.

MATERIALS AND METHODS

This retrospective study included 52 patients with liver disease who underwent a 3T MRE exam including both an investigational SE-EPI-based technique and a product GRE-based technique. Regions of interest (ROI) were placed on the elastograms to measure elastography-derived liver stiffness as well as the area included within the ROIs. The mean liver stiffness values and area of ROIs were compared.

RESULTS

The mean liver stiffness was 3.72 kilopascal (kPa) ± 1.29 using GRE MRE and 3.78 kPa ± 1.13 using SE-EPI MRE. Measurement of liver stiffness showed excellent agreement between the two pulse sequences with a mean bias of - 0.1 kPa (range - 1.8 to 1.7 kPa) between sequences. The mean measurable ROI area was higher with SE-EPI (313.8 cm² ± 213.8) than with the GRE technique (208.6 cm² ± 114.8), and the difference was statistically significant (P < 0.05).

CONCLUSIONS

Our data shows excellent agreement of measured liver stiffness between GRE and SE-EPI-based sequences at 3T. Our results show the advantage of a SE-EPI MRE sequence in terms of image quality, ROI size and acquisition time with equivalent liver stiffness measurements as compared to GRE-MRE sequence.

Inter-reader agreement of magnetic resonance imaging proton density fat fraction and its longitudinal change in a clinical trial of adults with nonalcoholic steatohepatitis

PURPOSE

To determine the inter-reader agreement of magnetic resonance imaging proton density fat fraction (PDFF) and its longitudinal change in a clinical trial of adults with nonalcoholic steatohepatitis (NASH).

STUDY TYPE

We performed a secondary analysis of a placebo-controlled randomized clinical trial of a bile acid sequestrant in 45 adults with NASH. A six-echo spoiled gradient-recalled-echo magnitude-based fat quantification technique was performed at 3 T. Three independent readers measured MRI-PDFF by placing one primary and two additional regions of interest (ROIs) in each segment at both time points. Cross-sectional agreement between the three readers was evaluated using intra-class correlation coefficients (ICCs) and coefficients of variation (CV). Additionally, we used Bland-Altman analyses to examine pairwise agreement between the three readers at baseline, end of treatment (EOT), and for longitudinal change.

RESULTS

Using all ROIs by all readers, mean PDFF at baseline, at EOT, and mean change in PDFF was 16.1%, 16.0%, and 0.07%, respectively. The 27-ROI PDFF measurements had 0.998 ICC and 1.8% CV at baseline, 0.998 ICC and 1.8% CV at EOT, and 0.997 ICC for longitudinal change. The 9-ROI PDFF measurements had corresponding values of 0.997 and 2.6%, 0.996 and 2.4%, and 0.994. Using 27 ROIs, the magnitude of the bias between readers for whole-liver PDFF measurement ranged from 0.03% to 0.06% points at baseline, 0.01% to 0.07% points at EOT, and 0.01% to 0.02% points for longitudinal change.

CONCLUSION

Inter-reader agreement for measuring whole-liver PDFF and its longitudinal change is high. 9-ROI measurements have only slightly lower agreement than 27-ROI measurements.

Feasibility and agreement of stiffness measurements using gradient-echo and spin-echo MR elastography sequences in unselected patients undergoing liver MRI

OBJECTIVE

  To evaluate the agreement of three MR elastography (MRE) sequences in patients undergoing liver MRI for clinical care.  Methods:  A cross-sectional retrospective study was performed with 223 patients referred for liver MRI, including 12 patients with liver iron overload. Data obtained with spin-echo (SE) and gradient-echo (GRE) MRE sequences were compared. Multiple linear regression adjusted for the presence of liver fat was also performed to assess the correlation between fat infiltration and stiffness measurements results. Agreement between two SE sequences was assessed in patients with liver iron overload.  Results: We found strong correlation between the GRE sequence and two SE sequences. Spearman's correlation coefficients between the GRE, SE, and SE-EPI MRE sequences in patients with liver R2* <75Hz were 0.74, 0.81, and 0.80. GRE-MRE failed in patients with liver R2* > 75 Hz. In this subgroup, the correlation coefficient between both SE-MRE sequences was 0.97. Liver fat did not interfere with the results.

CONCLUSION

In clinical setting, there is a high correlation between the GRE and SE MRE stiffness measurements, independently of the degree of liver fat infiltration measured by PDFF. A strong correlation between SE-MRE sequences is found even in patients with iron overload.  Advances in knowledge: Our study addresses liver iron and fat content simultaneously to describing the technical feasibility and correlation between different MRE sequences in consecutive unselected patients refereed for liver MRI. EPI SE-MRE should be considered an optimal alternative to assess liver fibrosis in patients in whom GRE-MRE failures, such as iron-overloaded, in pediatric, elderly, or severely ill populations.

Imaging of nonalcoholic fatty liver disease and its clinical utility

The prevalence of nonalcoholic fatty liver disease has been continuously rising over the last three decades and is projected to become the most common indication for liver transplantation in the near future. Its pathophysiology and complex interplay with diabetes and the metabolic syndrome are not as yet fully understood despite growing scientific interest and research. Modern imaging techniques offer significant assistance in this field by enabling the study of the liver noninvasively and evaluation of the degree of both steatosis and fibrosis, and even in attempting to diagnose the presence of inflammation (steatohepatitis). The derived measurements are highly precise, accurate and reproducible, performing better than biopsy in terms of quantification. In this article, these imaging techniques are overviewed and their performance regarding diagnosis, stratification and monitoring are evaluated. Their expanding role both in the research arena and in clinical practice along with their limitations is also discussed.

Donor Liver Small Droplet Macrovesicular Steatosis Is Associated With Increased Risk for Recipient Allograft Rejection

Although donor livers with <30% large droplet macrovesicular steatosis (MaS) and/or small droplet MaS (irrespective of percentage) are considered safe to use, this consensus is based on variable definitions of MaS subtypes and/or without a reproducible scoring system. We analyzed 134 donor liver biopsies from allografts transplanted at University of California at San Francisco between 2000 and 2015 to determine whether large and/or small droplet MaS is a risk factor for poor outcomes. Large droplet MaS was defined as a fat droplet occupying greater than one half of an individual hepatocyte, with nuclear displacement, and scored as the percentage of total parenchymal area replaced by large fat droplets on ×40 magnification. Small droplet MaS was defined as 1 to several discrete fat droplets, each occupying less than one half of an individual hepatocyte, and scored as the percentage of remaining hepatocytes (ie, hepatocytes not occupied by large fat droplets) containing small fat droplets on ×200 magnification (ie, small droplet MaS is the percentage of "remaining hepatocytes" with small fat droplets, and "remaining hepatocytes" is defined as 100% minus percent large droplet MaS). Thus, total MaS equals the sum of large and small droplet MaS, which cannot exceed 100%. Electronic medical records were reviewed to determine outcomes. There was an increased risk for acute cellular rejection (hazard ratio=2.5, P=0.0108) and bile duct loss suggestive of chronic ductopenic rejection (hazard ratio=2.4, P=0.0130) in donor livers with ≥30% small droplet MaS. Large droplet MaS (up to 60%) was not associated with adverse outcomes. Patient survival was not adversely affected by steatosis. Excellent agreement on the estimation of large (weighted κ=0.682) and small droplet MaS (weighted κ=0.780) was achieved. Our approach to donor steatosis scoring can identify liver allograft recipients at increased risk for rejection and highlights the importance of distinguishing between small and large droplet MaS in this evaluation.

Reliability of diagnosis from Mohs slides: interpersonal and intrapersonal agreement on basal cell carcinoma presence and histological subtype

BACKGROUND

The success of Mohs micrographic surgery (MMS) depends partly on the correct diagnosis of slides.

OBJECTIVES

To determine reliability of diagnosis from Mohs slides.

METHODS

This was a prospective study evaluating the reliability of diagnosis from Mohs slides of basal cell carcinoma (BCC) presence, BCC location on the slide and BCC subtype among six raters who independently assessed 50 Mohs slides twice with a 2-month interval. Slides were randomly selected whereby difficult-to-diagnose slides were oversampled. For each slide, a reference diagnosis was established by an expert panel. Cohen's kappa (κ) was calculated to determine levels of agreement interpersonally (rater vs. reference diagnosis) and intrapersonally (rater at T1 vs. T2). Multivariable logistic regression was used to determine independent risk factors for slides with interpersonal discordant diagnosis. The variables studied were BCC presence, whether a slide was scored as easy or difficult to diagnose, review duration of the 50 slides, profession and years of experience in diagnosis from Mohs slides.

RESULTS

Interpersonal and intrapersonal agreement were substantial on BCC presence (κ = 0·66 and 0·68) and moderate on BCC subtype (κ = 0·45 and 0·55). Slides that were scored as difficult to diagnose were an independent risk factor for interpersonal discordant diagnosis on BCC presence (odds ratio 3·54, 95% confidence interval 1·81-6·84).

CONCLUSIONS

Reliability of diagnosis from Mohs slides was substantial on BCC presence and moderate on BCC subtype. For slides that are scored difficult to diagnose, a second opinion is recommended to prevent misinterpretation and thereby recurrence of skin cancer.

Nonalcoholic fatty liver disease: different classifications concordance and relationship between degrees of morphological features and spectrum of the disease

The morphological features of nonalcoholic fatty liver disease (NAFLD) range from steatosis to nonalcoholic steatohepatitis (NASH) and cirrhosis. Liver biopsy remains the main tool for NASH diagnosis and many histological systems to diagnose and grade NAFLD were proposed. We evaluated the relationship among NAFLD activity score (NAS), histological diagnoses (non-NASH, possible NASH, and definite NASH), and histological algorithm proposed by Bedossa et al.; additionally the degrees of morphological features were semiquantified and correlated with non-NASH and NASH. Seventy-one liver biopsies were studied. The agreement among the three systems considering NASH and non-NASH was excellent (Κ = 0.96). Among the 22 biopsies with NAS 3-4, 72.7% showed to be NASH according to Bedossa's algorithm. The degree of steatosis, ballooning, lobular inflammation, and fibrosis stage were correlated with NASH (P < 0.001). Fibrosis stage 1 was also found in non-NASH. Over the spectrum of NAFLD, no association was observed between intensity of steatosis and fibrosis grade. The degrees of lobular inflammation showed association with fibrosis stage (P < 0.0001). In conclusion, there is agreement among different NAFLD classifications and NAS > 4 may be a better cutoff from which to consider NASH diagnosis; besides the highest degrees of steatosis, ballooning, inflammation, and fibrosis are associated with NASH.

The influence of dietary fat on liver fat accumulation

Obesity is a known risk factor for the development of non-alcoholic fatty liver disease (NAFLD); however, it has been suggested that dietary fat, both amount and composition, may play a pivotal role in its development, independent of body fatness. Studies that have investigated the role of dietary fat on liver fat accumulation are reasonably sparse. We review here the available work that has investigated the impact of dietary fat: amount, composition and frequency, on liver fat accumulation in human observational and intervention studies. Overall, it would seem that total calorie consumption, rather than dietary fat composition, is an important factor in the development of fatty liver disease in humans.

A diagnostic model for cirrhosis in patients with non-alcoholic fatty liver disease: an artificial neural network approach

BACKGROUND

Timely diagnosis of liver cirrhosis is vital for preventing further liver damage and giving the patient the chance of transplantation. Although biopsy of the liver is the gold standard for cirrhosis assessment, it has some risks and limitations and this has led to the development of new noninvasive methods to determine the stage and prognosis of the patients. We aimed to design an artificial neural network (ANN) model to diagnose cirrhosis patients with non-alcoholic fatty liver disease (NAFLD) using routine laboratory data.

METHODS

Data were collected from 392 patients with NAFLD by the Middle East Research Center in Tehran. Demographic variables, history of diabetes, INR, complete blood count, albumin, ALT, AST and other routine laboratory tests, examinations and medical history were gathered. Relevant variables were selected by means of feature extraction algorithm (Knime software) and were accredited by the experts. A neural network was developed using the MATLAB software.

RESULTS

The best obtained model was developed with two layers, eight neurons and TANSIG and PURLIN functions for layer one and output layer, respectively. The sensitivity and specificity of the model were 86.6% and 92.7%, respectively.

CONCLUSION

The results of this study revealed that the neural network modeling may be able to provide a simple, noninvasive and accurate method for diagnosing cirrhosis only based on routine laboratory data.

Nonalcoholic Fatty liver disease/non-alcoholic steatohepatitis in childhood: endocrine-metabolic "mal-programming"

CONTEXT

Nonalcoholic Fatty Liver Disease (NAFLD) is the major chronic liver disease in the pediatric population. NAFLD includes a broad spectrum of abnormalities (inflammation, fibrosis and cirrhosis), ranging from accumulation of fat (also known as steatosis) towards non-alcoholic steatohepatitis (NASH). The development of NAFLD in children is significantly increased.

EVIDENCE ACQUISITION

A literature search of electronic databases was undertaken for the major studies published from 1998 to today. The databases searched were: PubMed, EMBASE, Orphanet, Midline and Cochrane Library. We used the key words: "non-alcoholic fatty liver disease, children, non-alcoholic steatohepatitis and fatty liver".

RESULTS

NAFLD/NASH is probably promoted by "multiple parallel hits": environmental and genetic factors, systemic immunological disorders (oxidative stress, persistent-low grade of inflammation) as well as obesity and metabolic alterations (insulin resistance and metabolic syndrome). However its exact cause still underdiagnosed and unknown.

CONCLUSIONS

Pediatric NAFLD/NASH is emerging problem. Longitudinal follow-up studies, unfortunately still insufficient, are needed to better understand the natural history and outcome of NAFLD in children. This review focuses on the current knowledge regarding the epidemiology, pathogenesis, environmental, genetic and metabolic factors of disease. The review also highlights the importance of studying the underlying mechanisms of pediatric NAFLD and the need for complete and personalized approach in the management of NAFLD/NASH.