Use of imaging techniques for non-invasive assessment in the diagnosis and staging of non-alcoholic fatty liver disease

Associations Between Multiparametric US-Based Indicators and Pathological Status in Patients with Metabolic Associated Fatty Liver Disease

OBJECTIVE

Noninvasive evaluation of metabolic dysfunction-associated fatty liver disease (MAFLD) using ultrasonography holds significant clinical value. The associations between ultrasound (US)-based parameters and the pathological spectra remain unclear and controversial. This study aims to investigate the associations thoroughly.

METHODS

The participants with MAFLD undergoing liver biopsy and multiparametric ultrasonography were prospectively recruited from December 2020 to September 2022. Three US-based parameters, namely attenuation coefficient (AC), liver stiffness (LS) and dispersion slope (DS) were obtained. The relationship between these parameters and steatosis grades, inflammation grades and fibrosis stages was examined.

RESULTS

In this study with 116 participants, AC values significantly differed across distinct steatosis grades (p < 0.001), while DS and LS values varied among inflammation grades (p < 0.001) and fibrosis stages (p < 0.001). The area under the receiver operating characteristic curves (AUCs) of AC ranged from 0.82 to 0.84 for differentiating steatosis grades, while AUCs of LS ranged from 0.62 to 0.76 for distinguishing inflammation grades and 0.83-0.95 for discerning fibrosis stages. AUCs for DS ranged from 0.79 to 0.81 in discriminating inflammation grades and 0.80-0.88 for differentiating fibrosis stages. Subgroup analysis revealed that LS demonstrated different trends in inflammation grade but consistent trends in fibrosis stage across subgroups, whereas DS showed consistent trends for both inflammation grade and fibrosis stage across all subgroups.

CONCLUSION

AC values indicate the degree of hepatic steatosis but not inflammation or fibrosis. LS values are determined only by fibrosis stage and are not associated with inflammation grades. DS values are associated with both fibrosis and inflammation grades.

Omics-based biomarkers as useful tools in metabolic dysfunction-associated steatotic liver disease clinical practice: How far are we?

Unmet needs exist in metabolic dysfunction-associated steatotic liver disease (MASLD) risk stratification. Our ability to identify patients with MASLD with advanced fibrosis and at higher risk for adverse outcomes is still limited. Incorporating novel biomarkers could represent a meaningful improvement to current risk predictors. With this aim, omics technologies have revolutionized the process of MASLD biomarker discovery over the past decades. While the research in this field is thriving, much of the publication has been haphazard, often using single-omics data and specimen sets of convenience, with many identified candidate biomarkers but lacking clinical validation and utility. If we incorporate these biomarkers to direct patients' management, it should be considered that the roadmap for translating a newly discovered omics-based signature to an actual, analytically valid test useful in MASLD clinical practice is rigorous and, therefore, not easily accomplished. This article presents an overview of this area's current state, the conceivable opportunities and challenges of omics-based laboratory diagnostics, and a roadmap for improving MASLD biomarker research.

Development and validation of a novel non-invasive test for diagnosing nonalcoholic fatty liver disease in Chinese children

BACKGROUND

With the exploding prevalence of obesity, many children are at risk of developing nonalcoholic fatty liver disease. Using anthropometric and laboratory parameters, our study aimed to develop a model to quantitatively evaluate liver fat content (LFC) in children with obesity.

METHODS

A well-characterized cohort of 181 children between 5 and 16 years of age were recruited to the study in the Endocrinology Department as the derivation cohort. The external validation cohort comprised 77 children. The assessment of liver fat content was performed using proton magnetic resonance spectroscopy. Anthropometry and laboratory metrics were measured in all subjects. B-ultrasound examination was carried out in the external validation cohort. The Kruskal-Wallis test, Spearman bivariate correlation analyses, univariable linear regressions and multivariable linear regression were used to build the optimal predictive model.

RESULTS

The model was based on indicators including alanine aminotransferase, homeostasis model assessment of insulin resistance, triglycerides, waist circumference and Tanner stage. The adjusted R2 of the model was 0.589, which presented high sensitivity and specificity both in internal [sensitivity of 0.824, specificity of 0.900, area under curve (AUC) of 0.900 with a 95% confidence interval: 0.783-1.000] and external validation (sensitivity of 0.918 and specificity of 0.821, AUC of 0.901 with a 95% confidence interval: 0.818-0.984).

CONCLUSIONS

Our model based on five clinical indicators was simple, non-invasive, and inexpensive; it had high sensitivity and specificity in predicting LFC in children. Thus, it may be useful for identifying children with obesity who are at risk for developing nonalcoholic fatty liver disease.

Non-invasive testing and risk-stratification in patients with MASLD

The development and validation of non-invasive fibrosis tests (NITs) has changed clinical practice in Hepatology over the last 15 years. Metabolic associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease (NAFLD), is the most prevalent liver disease in western countries, with up to a third of the unselected adult population affected. In this article, we review the use of NITs in the diagnosis and staging of MASLD. We discuss their use in the diagnosis of steatosis, steatohepatitis and fibrosis and critically evaluate recently published data. These NITs include a variety of approaches, such as serum markers like FIB-4, pro-C3 and ELF, imaging techniques like Fibroscan® and MRE, and combined scores like Agile 3+ and Agile 4, offering a range of options for healthcare providers. Furthermore, these non-invasive tests also serve as valuable prognostic tools, allowing for better risk assessment and improved patient management, particularly in predicting liver-related events and overall mortality.

Reliability and stability of ultrasound-guided attenuation parameter in evaluating hepatic steatosis

PURPOSE

This study aimed to explore the reliability and stability of ultrasound-guided attenuation parameter (UGAP) values obtained by two measuring methods and different measuring times.

METHODS

Patients who underwent liver UGAP examinations in our hospital from September 2022 to December 2022 were retrospectively analyzed. The clinical data and UGAP measurements results were collected. Two different measuring methods: static single-frame multi-point measuring and dynamic multi-frame single-point measuring, were performed for each patient, and 10 UGAP values of each measuring method were recorded. The medians of the UGAP values of the 1st-3rd, 1st-5th, 1st-7th and 1st-10th by each measuring method were taken as the final UGAP values of measuring 3, 5, 7 and 10 times. The UGAP values obtained by the two different measuring methods and different measuring times (3, 5, 7 or 10 times) were compared.

RESULTS

206 patients were included in this study. There was no statistical difference between UGAP values measured by static single-frame multi-point measuring and dynamic multi-frame single-point measuring (P = 0.689, P = 0.270, P = 0.298, P = 0.091), regardless of measuring times (3, 5, 7, 10 times). No significant difference between the UGAP values obtained by 3, 5, 7 and 10 measurements was found (P = 0.554, P = 0.916).

CONCLUSION

The UGAP values obtained by the two different measuring methods and different measuring times (3, 5, 7 and 10 times) are stable and reliable. Additionally, 3 times of UGAP measurements might be enough for each patient in clinical practice.

The Liver in Heart Failure: From Biomarkers to Clinical Risk

Heart failure (HF) is a clinical syndrome due to heart dysfunction, but in which other organs are also involved, resulting in a complex multisystemic disease, burdened with high mortality and morbidity. This article focuses on the mutual relationship between the heart and liver in HF patients. Any cause of right heart failure can cause hepatic congestion, with important prognostic significance. We have analyzed the pathophysiology underlying this double interaction. Moreover, we have explored several biomarkers and non-invasive tests (i.e., liver stiffness measurement, LSM) potentially able to provide important support in the management of this complex disease. Cardiac biomarkers have been studied extensively in cardiology as a non-invasive diagnostic and monitoring tool for HF. However, their usefulness in assessing liver congestion in HF patients is still being researched. On the other hand, several prognostic scores based on liver biomarkers in patients with HF have been proposed in recent years, recognizing the important burden that liver involvement has in HF. We also discuss the usefulness of a liver stiffness measurement (LSM), which has been recently proposed as a reliable and non-invasive method for assessing liver congestion in HF patients, with therapeutic and prognostic intentions. Lastly, the relationship between LSM and biomarkers of liver congestion is not clearly defined; more research is necessary to establish the clinical value of biomarkers in assessing liver congestion in HF patients and their relationship with LSM.

Differences in liver and mortality outcomes of non-alcoholic fatty liver disease by race and ethnicity: A longitudinal real-world study

BACKGROUND/AIMS

Understanding of nonalcoholic fatty liver disease (NAFLD) continues to expand, but the relationship between race and ethnicity and NAFLD outside the use of cross-sectional data is lacking. Using longitudinal data, we investigated the role of race and ethnicity in adverse outcomes in NAFLD patients.

METHODS

Patients with NAFLD confirmed by imaging via manual chart review from any clinics at Stanford University Medical Center (1995-2021) were included. Primary study outcomes were incidence of liver events and mortality (overall and non-liver related).

RESULTS

The study included 9,340 NAFLD patients: White (44.1%), Black (2.29%), Hispanic (27.9%), and Asian (25.7%) patients. For liver events, the cumulative 5-year incidence was highest among White (19.1%) patients, lowest among Black (7.9%) patients, and similar among Asian and Hispanic patients (~15%). The 5-year and 10-year cumulative overall mortality was highest for Black patients (9.2% and 15.0%, respectively, vs. 2.5-3.5% and 4.3-7.3% in other groups) as well as for non-liver mortality. On multivariable regression analysis, compared to White patients, only Asian group was associated with lower liver-related outcomes (aHR: 0.83, P=0.027), while Black patients were at more than two times higher risk of both non-liver related (aHR: 2.35, P=0.010) and overall mortality (aHR: 2.13, P=0.022) as well as Hispanic patients (overall mortality: aHR: 1.44, P=0.022).

CONCLUSION

Compared to White patients, Black patients with NAFLD were at the highest risk for overall and non-liver-related mortality, followed by Hispanic patients with Asian patients at the lowest risk for all adverse outcomes. Culturally sensitive and appropriate programs may be needed for more successful interventions.

Precision Medicine in Fatty Liver Disease/Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease, and is related to fatal and non-fatal liver, metabolic, and cardiovascular complications. Its non-invasive diagnosis and effective treatment remain an unmet clinical need. NAFLD is a heterogeneous disease that is most commonly present in the context of metabolic syndrome and obesity, but not uncommonly, may also be present without metabolic abnormalities and in subjects with normal body mass index. Therefore, a more specific pathophysiology-based subcategorization of fatty liver disease (FLD) is needed to better understand, diagnose, and treat patients with FLD. A precision medicine approach for FLD is expected to improve patient care, decrease long-term disease outcomes, and develop better-targeted, more effective treatments. We present herein a precision medicine approach for FLD based on our recently proposed subcategorization, which includes the metabolic-associated FLD (MAFLD) (i.e., obesity-associated FLD (OAFLD), sarcopenia-associated FLD (SAFLD, and lipodystrophy-associated FLD (LAFLD)), genetics-associated FLD (GAFLD), FLD of multiple/unknown causes (XAFLD), and combined causes of FLD (CAFLD) as well as advanced stage fibrotic FLD (FAFLD) and end-stage FLD (ESFLD) subcategories. These and other related advances, as a whole, are expected to enable not only improved patient care, quality of life, and long-term disease outcomes, but also a considerable reduction in healthcare system costs associated with FLD, along with more options for better-targeted, more effective treatments in the near future.

Silymarin for treatment of adults with nonalcoholic fatty liver disease

This is a protocol for a Cochrane Review (intervention). The objectives are as follows:

To evaluate the benefits and harms of silymarin in adults with nonalcoholic fatty liver disease (NAFLD).

The steatosis-associated fibrosis estimator (SAFE) score: A tool to detect low-risk NAFLD in primary care

BACKGROUND

NAFLD is common in primary care. Liver fibrosis stage 2 or higher (≥F2) increases future risk of morbidity and mortality. We developed and validated a score to aid in the initial assessment of liver fibrosis for NAFLD in primary care.

METHODS

Data from patients with biopsy-proven NAFLD were extracted from the NASH Clinical Research Network observational study ( n = 676). Using logistic regression and machine-learning methods, we constructed prediction models to distinguish ≥F2 from F0/1. The models were tested in participants in a trial ("FLINT," n = 280) and local patients with NAFLD with magnetic resonance elastography data ( n = 130). The final model was applied to examinees in the National Health and Nutrition Examination Survey (NHANES) III ( n = 11,953) to correlate with long-term mortality.

RESULTS

A multivariable logistic regression model was selected as the Steatosis-Associated Fibrosis Estimator (SAFE) score, which consists of age, body mass index, diabetes, platelets, aspartate and alanine aminotransferases, and globulins (total serum protein minus albumin). The model yielded areas under receiver operating characteristic curves ≥0.80 in distinguishing F0/1 from ≥F2 in testing data sets, consistently higher than those of Fibrosis-4 and NAFLD Fibrosis Scores. The negative predictive values in ruling out ≥F2 at SAFE of 0 were 88% and 92% in the two testing sets. In the NHANES III set, survival up to 25 years of subjects with SAFE < 0 was comparable to that of those without steatosis ( p = 0.34), whereas increasing SAFE scores correlated with shorter survival with an adjusted HR of 1.53 ( p < 0.01) for subjects with SAFE > 100.

CONCLUSION

The SAFE score, which uses widely available variables to estimate liver fibrosis in patients diagnosed with NAFLD, may be used in primary care to recognize low-risk NAFLD.

Liver fat analysis using optimized support vector machine with support vector regression

BACKGROUND

Fatty liver disease is a common condition caused by excess fat in the liver. It consists of two types: Alcoholic Fatty Liver Disease, also called alcoholic steatohepatitis, and Non-Alcoholic Fatty Liver Disease (NAFLD). As per epidemiological studies, fatty liver encompasses 9% to 32% of the general population in India and affects overweight people.

OBJECTIVE

An Optimized Support Vector Machine with Support Vector Regression model is proposed to evaluate the volume of liver fat by image analysis (LFA-OSVM-SVR).

METHOD

The input computed tomography (CT) liver images are collected from the Chennai liver foundation and Liver Segmentation (LiTS) datasets. Here, input datasets are pre-processed using Gaussian smoothing filter and bypass filter to reduce noise and improve image intensity. The proposed U-Net method is used to perform the liver segmentation. The Optimized Support Vector Machine is used to classify the liver images as fatty liver image and normal images. The support vector regression (SVR) is utilized for analyzing the fat in percentage.

RESULTS

The LFA-OSVM-SVR model effectively analyzed the liver fat from CT scan images. The proposed approach is activated in python and its efficiency is analyzed under certain performance metrics.

CONCLUSION

The proposed LFA-OSVM-SVR method attains 33.4%, 28.3%, 25.7% improved accuracy with 55%, 47.7%, 32.6% lower error rate for fatty image classification and 30%, 21%, 19.5% improved accuracy with 57.9%, 46.5%, 31.76% lower error rate for normal image classificationthan compared to existing methods such as Convolutional Neural Network (CNN) with Fractional Differential Enhancement (FDE) (CNN-FDE), Fully Convolutional Networks (FCN) and Non-negative Matrix Factorization (NMF) (FCN-NMF), and Deep Learning with Fully Convolutional Networks (FCN) (DL-FCN).

Adipose tissue dysfunction and visceral fat are associated with hepatic insulin resistance and severity of NASH even in lean individuals

BACKGROUND & AIMS

Non-alcoholic fatty liver disease (NAFLD) is a heterogeneous disorder, but the factors that determine this heterogeneity remain poorly understood. Adipose tissue dysfunction is causally linked to NAFLD since it causes intrahepatic triglyceride (IHTG) accumulation through increased hepatic lipid flow, due to insulin resistance and pro-inflammatory adipokines release. While many studies in NAFLD have looked at total adiposity (i.e. mainly subcutaneous fat, SC-AT), it is still unclear the possible impact of visceral fat (VF). Thus, we investigated how VF versus SC-AT was related to NAFLD severity in lean, overweight and obese individuals versus lean controls.

METHODS

Thirty-two non-diabetic NAFLD with liver biopsy (BMI 21.4-34.7 kg/m² ) and eight lean individuals (BMI 19.6-22.8 kg/m² ) were characterized for fat distribution (VF, SC-AT and IHTG by magnetic resonance imaging), lipolysis and insulin resistance by tracer infusion, free fatty acids (FFAs) and triglyceride (TAG) concentration and composition (by mass spectrometry).

RESULTS

Intrahepatic triglyceride was positively associated with lipolysis, adipose tissue insulin resistance (Adipo-IR), TAG concentrations, and increased saturated/unsaturated FFA ratio. Compared to controls VF was higher in NAFLD (including lean individuals), increased with fibrosis stage and associated with insulin resistance in liver, muscle and adipose tissue, increased lipolysis and decreased adiponectin levels. Collectively, our results suggest that VF accumulation, given its location close to the liver, is one of the major risk factors for NAFLD.

CONCLUSIONS

These findings propose VF as an early indicator of NAFLD progression independently of BMI, which may allow for evidence-based prevention and intervention strategies.

Butyrate to combat obesity and obesity-associated metabolic disorders: Current status and future implications for therapeutic use

Evidence is increasing that disturbances in the gut microbiome may play a significant role in the etiology of obesity and type 2 diabetes. The short chain fatty acid butyrate, a major end product of the bacterial fermentation of indigestible carbohydrates, is reputed to have anti-inflammatory properties and positive effects on body weight control and insulin sensitivity. However, whether butyrate has therapeutic potential for the treatment and prevention of obesity and obesity-related complications remains to be elucidated. Overall, animal studies strongly indicate that butyrate administered via various routes (e.g., orally) positively affects adipose tissue metabolism and functioning, energy and substrate metabolism, systemic and tissue-specific inflammation, and insulin sensitivity and body weight control. A limited number of human studies demonstrated interindividual differences in clinical effectiveness suggesting that outcomes may depend on the metabolic, microbial, and lifestyle-related characteristics of the target population. Hence, despite abundant evidence from animal data, support of human data is urgently required for the implementation of evidence-based oral and gut-derived butyrate interventions. To increase the efficacy of butyrate-focused interventions, future research should investigate which factors impact treatment outcomes including baseline gut microbial activity and functionality, thereby optimizing targeted-interventions and identifying individuals that merit most from such interventions.

Hepatic Steatosis Index and the Risk of Type 2 Diabetes Mellitus in China: Insights from a General Population-Based Cohort Study

Purpose

In the Chinese population, we looked at the relationship between the hepatic steatosis index (HSI) and the risk of type 2 diabetes mellitus (T2DM).

Methods

To evaluate the association between HSI and the risk of T2DM, Cox regression models were employed. Hazard ratios (HR) and 95 percent confidence intervals (CI) were computed. A stratified analysis with interaction testing was also carried out. Additionally, we evaluated the incremental predictive value of the HSI over the established risk factors using the C-statistic, the IDI, and the NRI.

Results

During a median follow-up period of 2.97 years, 433 (1.97%) participants developed new-onset T2DM. The smoothing curve fit plot showed a positive correlation between HSI and the risk of T2DM. After adjusting for all noncollinear variables, the risk of T2DM increased by 62% for every 1 standard deviation (SD) increase in HSI. Subgroup analysis indicated that higher HSI levels were associated with a higher risk of T2DM in those aged < 40 years. The addition of HSI enhanced the reclassification and discrimination of established risk factors, with an IDI of 0.027 and an NRI of 0.348 (both P < 0.001).

Conclusion

Our findings suggest that an elevated HSI is substantially associated with a greater risk of T2DM in the Chinese population. HSI has the potential to be an available and supplementary monitoring method for the management of T2DM risk stratification in the Chinese population.

Noninvasive Risk Stratification for Nonalcoholic Fatty Liver Disease Among Living Liver Donor Candidates: A Proposed Algorithm

To reduce waitlist mortality, living donor liver transplantation (LDLT) has increased over the past decade in the United States, but not at a rate sufficient to completely mitigate organ shortage. As a result, there are ongoing efforts to expand the living liver donor pool. Simultaneously, the prevalence of nonalcoholic fatty liver disease (NAFLD) in the general population has increased, which has significant implications on the pool of potential living liver donors. As such, a clinical assessment algorithm that exhaustively evaluates for NAFLD and fibrosis is critical to the safe expansion of LDLT. An ideal algorithm would employ safe and noninvasive methods, relying on liver biopsy only when necessary. While exclusion of NAFLD and fibrosis by noninvasive means is widely studied within the general population, there are no well-accepted guidelines for evaluation of living donors using these modalities. Here we review the current literature regarding noninvasive NALFD and fibrosis evaluation and propose a potential algorithm to apply these modalities for the selection of living liver donors.

A novel radiomics signature based on T2-weighted imaging accurately predicts hepatic inflammation in individuals with biopsy-proven nonalcoholic fatty liver disease: a derivation and independent validation study

Background

Currently, there are no effective methods for assessing hepatic inflammation without resorting to histological examination of liver tissue obtained by biopsy. T2-weighted images (T2WI) are routinely obtained from liver magnetic resonance imaging (MRI) scan sequences. We aimed to establish a radiomics signature based on T2WI (T2-RS) for assessment of hepatic inflammation in people with nonalcoholic fatty liver disease (NAFLD).

Methods

A total of 203 individuals with biopsy-confirmed NAFLD from two independent Chinese cohorts with liver MRI examination were enrolled in this study. The hepatic inflammatory activity score (IAS) was calculated by the unweighted sum of the histologic scores for lobular inflammation and ballooning. One thousand and thirty-two radiomics features were extracted from the localized region of interest (ROI) in the right liver lobe of T2WI and, subsequently, selected by minimum redundancy maximum relevance and least absolute shrinkage and selection operator (LASSO) methods. The T2-RS was calculated by adding the selected features weighted by their coefficients.

Results

Eighteen radiomics features from Laplacian of Gaussian, wavelet, and original images were selected for establishing T2-RS. The T2-RS value differed significantly between groups with increasing grades of hepatic inflammation (P<0.01). The T2-RS yielded an area under the receiver operating characteristic (ROC) curve (AUROC) of 0.80 [95% confidence interval (CI): 0.71-0.89] for predicting hepatic inflammation in the training cohort with excellent calibration. The AUROCs of T2-RS in the internal cohort and external validation cohorts were 0.77 (0.61-0.93) and 0.75 (0.63-0.84), respectively.

Conclusions

The T2-RS derived from radiomics analysis of T2WI shows promising utility for predicting hepatic inflammation in individuals with NAFLD.

The role of elastography in non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide and its prevalence is even higher in patients with risk factors such as type 2 diabetes and obesity. Liver biopsy is the gold standard for diagnosis of non-alcoholic steatohepatitis (NASH), particularly for the assessment of fibrosis stage that is a key prognostic factor. Noninvasive methods for assessment of liver fibrosis are a huge need in contemporary hepatology in order to stratify patient's risk of advanced and progressive liver disease. In this perspective different imaging techniques have been developed in last decades and showed high performance in liver fibrosis evaluation. Strengths and weaknesses of all imaging methods are summarized in this review.

Assessment of factors affecting washout appearance of hepatocellular carcinoma on CT

OBJECTIVES

To identify independent imaging and histopathologic factors that affect washout appearance of hepatocellular carcinoma (HCC) in CT images.

METHODS

This retrospective study included 264 patients who had undergone surgical resection for treatment-naïve single HCC between January 2014 and December 2015 and had available preoperative multiphasic CT images. Two reviewers evaluated the CT imaging features of HCC using LI-RADS v2018. The "washout" was visually assessed in portal venous or equilibrium phases. Depending on the presence of washout appearance of HCC, all patients were divided into "washout" (n = 228) and "no washout" (n = 36) groups. Multivariable logistic regression analysis was used to identify factors associated with the absence of washout appearance of HCC.

RESULTS

A total of 264 HCCs (median size, 2.6 cm) were analyzed. Histologically proven hepatic steatosis (macrovesicular steatosis ≥ 5%) (odds ratio [OR], 2.65; 95% confidence interval [CI], 1.05-6.74; p = 0.040), tumor capsule on histopathology (OR, 0.17; 95% CI, 0.06-0.50; p = 0.001), and mosaic appearance on CT image (OR, 0.34; 95% CI, 0.14-0.85; p = 0.021) were independent factors associated with the absence of washout appearance of HCC. In 189 patients with available unenhanced CT images, CT-diagnosed hepatic steatosis was also an independent factor for the absence of washout appearance of HCC (OR, 9.26; 95% CI, 3.06-28.02; p < 0.001).

CONCLUSIONS

Washout appearance of HCC in CT images could be obscured in both histologically proven hepatic steatosis and CT-diagnosed hepatic steatosis, and could be enhanced with tumor capsule on histopathology and mosaic appearance on CT image.

KEY POINTS

• Hepatic steatosis is an independent factor related to the absence of washout appearance of hepatocellular carcinoma in CT images, in both histologically proven hepatic steatosis and CT-diagnosed hepatic steatosis. • Both histologically proven hepatic steatosis and CT-diagnosed hepatic steatosis have higher odds of absence of washout appearance of hepatocellular carcinoma compared to non-steatotic liver. • Tumor capsule on histopathology and mosaic appearance on CT image are independent factors that enhance the probability that washout appearance of hepatocellular carcinoma is visible.

Clinical and Biochemical Predictors of Nonalcoholic Fatty Liver Disease among Type 2 Diabetes Mellitus Patients at Primary Health Care Level in South Western Saudi Arabia

Objectives: To predict the role of different clinical and biochemical parameters in identifying nonalcoholic fatty liver disease (NAFLD) among patients with type 2 diabetes mellitus (T2DM) in Abha city, southwestern Saudi Arabia. Methods: A stratified random sample was selected. A detailed clinical and biochemical examinations were performed. Using portable abdominal ultrasound examination, NAFLD was identified. The study used receiver operating characteristic (ROC) analysis. Results: The study covered 237 T2DM patients. NAFLD was detected among 174 patients. Area under the curve (AUC) calculations showed that the ability of age, duration of DM in years, and body mass index to predict NAFLD was poor (AUC < 0.6). Similarly, biochemical factors like HbA1c%, AST, cholesterol, triglycerides, HDL, LDL, and VLDL were poor in discriminating between those with and without NAFLD among T2DM. On the other hand, the ability of ALT to predict NAFLD among T2DM was good (AUC = 0.701, 95% CI: 0.637–0.761). The analysis identified the optimal cutoff point of ALT to be ≤22.1 nmol/L. The corresponding sensitivity was 60.7% (95% CI: 53.0–68.0) and specificity was 62.5% (95% CI: 49.5–74.3). Conclusions: Early identification of NAFLD among T2DM is important. A threshold cutoff value of 22.1 nmol/L of ALT has been identified to predict NAFLD. They should be referred for ultrasound examination for NAFLD.