Over the past few decades, the rising burden of metabolic disease, including type 2 diabetes, prediabetes, obesity, and metabolic dysfunction-associated steatotic liver disease, has corresponded with fundamental shifts in the landscape of heart failure (HF) epidemiology, including the rising prevalence of HF with preserved ejection fraction. It has become increasingly important to understand the role of extracardiac contributors and interorgan communication in the pathophysiology and phenotypic heterogeneity of HF. Whereas traditional epidemiological strategies have separately examined individual contributions of specific comorbidities to HF risk, these approaches may not capture the shared mechanisms and more complex, bidirectional relationships between cardiac and noncardiac comorbidities. In this review, we highlight the cardiac, kidney, liver, and metabolism multiorgan interactions and pathways that complicate HF development and progression and propose research strategies to further understand HF in the context of multiple organ disease. This includes evolving epidemiological approaches such as multiomics and machine learning which may better capture common underlying mechanisms and interorgan crosstalk. We review existing preclinical models of HF and how they have enhanced our understanding of the role of multiorgan disease in the development of HF subtypes. We suggest recommendations as to how clinical practice across multiple specialties should screen for and manage multiorgan involvement in HF. Finally, recognizing the advent of novel combinatorial therapeutic agents that may have multiple indications across the cardiac-kidney-liver metabolism continuum, we review the current clinical trials landscape. We specifically highlight a pressing need for the design of more inclusive trials that examine the contributions of multimorbidity and incorporate multiorgan end points, which we propose may lead to outcomes that are evermore clinically relevant today.

Nonalcoholic fatty liver disease (NAFLD) is a major public health problem and the most common chronic liver disease today. In Korea, the prevalence and incidence of NAFLD are currently very high, causing a serious social burden. Perfluoroalkyl substances (PFAS) have been consistently implicated as a potential cause of NAFLD, but research in Koreans is limited.

Using data from the 4th Korean National Environmental Health Survey (KoNEHS, n = 2859), we investigated the association between PFAS blood levels and NAFLD. Multivariable logistic regression models were used to calculate odds ratios (ORs) for the effects of PFAS. A mediation analysis was also conducted to examine the mediating effect of obesity. Finally, weighted quantile sum (WQS) and G-computation methods were implemented to evaluate the joint effect of PFAS mixtures. Hepatic steatosis index was used as a diagnostic tool for NAFLD.

Through multivariable logistic regression, statistically significant associations with NAFLD were observed for perfluorooctanoic acid (PFOA) (OR 1.09-1.39), perfluorooctansulfonate (PFOS) (1.09-1.40), perfluorohexanesulfonic acid (PFHxS) (1.04-1.22), perfluorononanoic acid (PFNA) (1.12-1.42), and total PFAS (1.21-1.81). We also found that obesity was a significant mediator for PFOA, PFNA, and total PFAS. The ORs for NAFLD obtained by WQS and G-computation methods in the multivariable adjusted model were 1.10-1.46 and 1.08-1.32, respectively.

This study confirmed a significant association between some PFAS and increased odds of NAFLD. Excessive exposure to PFAS might explain the high prevalence and incidence of chronic liver disease in Koreans. Long-term cohort studies are needed to assess geographic and occupational exposures in the Korean population.

To evaluate the correlation between liver viscosity, as measured by shear wave dispersion (SWD), and fibrosis and inflammation in patients with autoimmune hepatitis (AIH). Additionally, to assess its potential as a non-invasive biomarker for hepatic fibrosis compared to shear wave elastography (SWE).

This prospective study included 25 AIH patients who underwent pre-biopsy SWD and SWE measurements using the SuperSonic Mach30 system. Liver biopsy samples were assessed for fibrosis using the Scheuer grading system and for inflammation using the modified Hepatic Activity Index (mHAI). Correlations between viscosity, elastography, fibrosis, and inflammation were analysed using Spearman's correlation coefficients.

Viscosity demonstrated a significant correlation with fibrosis stages (Spearman's coefficient: 0.58, p = 0.002), while SWE showed a weaker correlation (Spearman's coefficient: 0.50, p = 0.01). Viscosity measurements also correlated moderately with the mHAI score (Spearman's coefficient: 0.62, p = 0.001). Subgroup analyses revealed weak to moderate correlations between viscosity and mHAI components across fibrosis stages.

Our study suggests that viscosity may be better than SWE as a non-invasive marker for assessing hepatic fibrosis in AIH, particularly in the pre-treatment period when inflammation levels are elevated. However, we could not conclusively determine the relationship between viscosity and hepatic inflammation, as a small sample size limited our findings. Further research with a larger cohort of AIH patients is necessary to better understand the correlation between viscosity and inflammation in this rare condition.

Objectives: We aimed to develop and validate machine learning (ML) models that integrate clinical and laboratory data for the non-invasive prediction of metabolic dysfunction-associated steatohepatitis (MASH) in an obese population. Methods: In this retrospective study, clinical and laboratory data were collected from obese patients undergoing bariatric surgery. The cohort was divided using stratified random sampling, and optimal features were selected with SHapley Additive exPlanations (SHAP). Various ML models, including K-nearest neighbors, linear support vector machine, radial basis function support vector machine, Gaussian process, random forest, multilayer perceptron, adaptive boosting, and naïve Bayes, were developed through cross-validation and hyperparameter tuning. Diagnostic performance was assessed via the area under the curve (AUC) in both training and validation sets. Results: A total of 558 patients were analyzed, with 390 in the training set and 168 in the validation set. In the training cohort, the median age was 35 years, the median body mass index (BMI) was 39.8 kg/m2, 39.0% were male, 37.9% had diabetes mellitus, and 62.8% were diagnosed with MASH. The validation cohort had a median age of 34.1 years, a median BMI of 42.5 kg/m2, 41.7% male, 32.7% with diabetes, and 39.9% with MASH. Among the models, the random forest achieved the highest performance among the models with AUC values of 0.94 in the training set and 0.88 in the validation set. The Gaussian process model attained an AUC of 0.97 in the training cohort but 0.79 in the validation cohort, while the other models achieved AUC values ranging from 0.63 to 0.88 in the training cohort and 0.62 to 0.75 in the validation set. Conclusions: ML models, particularly the random forest, effectively predict MASH using readily available data, offering a promising non-invasive alternative to conventional serological scoring. Prospective studies and external validations are needed to further establish clinical utility.

Diabetes mellitus (DM) is associated with the development and progression of metabolic dysfunction-associated steatotic liver disease (MASLD). In our study, we aimed to evaluate the relationship between liver stiffness (LS) and galectin-3 levels in patients diagnosed with prediabetes.

A total of 120 participants were included in this prospective and cross-sectional study, comprising 40 patients with prediabetes, 40 patients with type 2 DM and 40 individuals with normal glucose metabolism. Human galectin-3 levels were measured using Enzyme-Linked Immunosorbent Assay (ELISA) with Human Galectin-3 kits. LS measurements were performed using the FibroScan® Mini 430 device (Echosens, France).

In our study, we found that Fib-4 index, LS and galectin-3 levels were increased in patients with prediabetes. Another significant finding was that hemoglobin A1c (HbA1c) and galectin-3 levels were higher in patients with LS value ≥8 kPa and both HbA1c and galectin-3 levels were independently associated with LS.

Considering the increased prevalence of MASLD in prediabetes, we recommend early assessment of LS and measurement of galectin-3 levels in these patients.

To investigate whether there is any effect of preprandial and postprandial states of patients on Ultrasound-derived fat fraction(UDFF) in liver fat content measurement.

A retrospective study was conducted on 1596 patients who underwent UDFF from January to September 2024; UDFF measurements were performed by a sonographer, who repeated each measurement 5 times before and after meals, respectively, and finally expressed them as the mean; then paired t-tests and analyses of variance (ANOVA) were used to compare the differences in preprandial and postprandial UDFF and Auto p-SWE( Auto point shear wave elastography) values among groups, and linear regression was used to analyze the differences in preprandial and postprandial UDFF and Auto p-SWE values between each group.

The study enrolled 1036 patients(491 males and 545 females), aged 18-89 years, mean age (56.50 ± 14.67) years. The differences in UDFF and Auto p-SWE values between the group eating protein and fatty foods (n = 613) and the group eating light foods (n = 423) were not statistically significant (p > 0.05); the differences in UDFF and Auto p-SWE values between the group with a body mass index(BMI) < 25 kg/m2 (n = 703) and the group with a BMI ≥ 25 kg/m2 (n = 333) were statistically significant (p < 0.05). Preprandial and postprandiall UDFF and Auto p-SWE values were highly positively correlated in the eating group, the protein and greasy food group, and the light food group (r = 0.985, 0.983, 0.988, r = 0.834, 0.849, 0.810, all p < 0.001).

UDFF has good consistency in the measurement of liver fat content in preprandial and postprandial states.

This study sought to assess the capabilities of large language models (LLMs) in identifying clinically significant metabolic dysfunction-associated steatotic liver disease (MASLD).

We included individuals from NHANES 2017-2018. The validity and reliability of MASLD diagnosis by GPT-3.5 and GPT-4 were quantitatively examined and compared with those of the Fatty Liver Index (FLI) and United States FLI (USFLI). A receiver operating characteristic curve was conducted to assess the accuracy of MASLD diagnosis via different scoring systems. Additionally, GPT-4V's potential in clinical diagnosis using ultrasound images from MASLD patients was evaluated to provide assessments of LLM capabilities in both textual and visual data interpretation.

GPT-4 demonstrated comparable performance in MASLD diagnosis to FLI and USFLI with the AUROC values of .831 (95% CI .796-.867), .817 (95% CI .797-.837) and .827 (95% CI .807-.848), respectively. GPT-4 exhibited a trend of enhanced accuracy, clinical relevance and efficiency compared to GPT-3.5 based on clinician evaluation. Additionally, Pearson's r values between GPT-4 and FLI, as well as USFLI, were .718 and .695, respectively, indicating robust and moderate correlations. Moreover, GPT-4V showed potential in understanding characteristics from hepatic ultrasound imaging but exhibited limited interpretive accuracy in diagnosing MASLD compared to skilled radiologists.

GPT-4 achieved performance comparable to traditional risk scores in diagnosing MASLD and exhibited improved convenience, versatility and the capacity to offer user-friendly outputs. The integration of GPT-4V highlights the capacities of LLMs in handling both textual and visual medical data, reinforcing their expansive utility in healthcare practice.

Metabolic dysfunction associated steatohepatitis (MASH), previously referred to as nonalcoholic steatohepatitis (NASH), has emerged as one of the leading indications for liver transplantation in the United States. The disease is associated with increased cardiovascular mortality in patients with early-stage liver fibrosis and a heightened risk of hepatic complications in those with advanced fibrosis. Despite its growing prevalence and significant healthcare burden, there were no approved drugs to treat this chronic disease. In March 2024, Resmetirom, a selective thyroid hormone receptor-beta agonist, became the first drug to receive FDA approval for the treatment of patients with MASH and fibrosis stages F2/F3. This accelerated approval was granted based on significantly higher rates of MASH resolution and fibrosis.

This review summarizes the current literature on the mechanism of action, preclinical data, pharmacokinetics, clinical efficacy, indications, and contraindications of resmetirom in the management of patients with MASH.

The approval of resmetirom for patients with MASH and moderate to advanced hepatic fibrosis is a major advance in the management of MASH. The recent positive results of the ESSENCE trial of semaglutide, if associated with conditional approval, may offer clinicians two options to treat MASH in patients with moderate to advanced fibrosis.

Several anthropometric indices, such as body mass index and waist circumference, have been used as clinical screening tools for the prediction of nonalcoholic fatty liver disease (NAFLD). To further refine these clinical tools for NAFLD, the body roundness index (BRI) has recently been evaluated. In this systematic review and meta-analysis, the objective was to evaluate the relationship and predictive capability of the BRI in identifying NAFLD.

A comprehensive search was conducted in PubMed, Embase, Web of Science, and Scopus up to December 31, 2024. Eligibility criteria included observational studies on adults (≥ 18 years old) with measured BRI and its association with NAFLD. The Joanna Briggs Institute tool was used for risk of bias assessment. Meta-analyses used random-effects models to pool data on mean difference, odds ratio, sensitivity, specificity, and the area under the curve (AUC), with heterogeneity and publication bias assessed.

Ten studies involving 59,466 participants were included. The pooled mean difference in BRI between the NAFLD and non-NAFLD groups was 1.73 (95% confidence interval [CI]: 1.31-2.15). The pooled sensitivity and specificity of BRI for diagnosing NAFLD were 0.806 and 0.692, respectively. The pooled AUC for BRI was 0.803 (95% CI: 0.775-0.830), indicating good diagnostic accuracy. Unlike subgroup analysis by country, subgroup analysis by sex showed no significant differences. Higher BRI values were associated with increased odds of NAFLD (pooled OR = 2.87, 95% CI: 1.39; 5.96). Studies provided mixed results on the predictive ability of BRI compared to other indices like body mass index, mostly favoring BRI over conventional indices.

BRI demonstrates a good diagnostic performance for NAFLD, suggesting it may be a valuable clinical tool for NAFLD assessment. Further research is necessary to validate these findings and strengthen the evidence base.

A novel noninvasive score, Agile-4 score, combining liver stiffness measurements, aspartate aminotransferase/alanine aminotransferase, platelet count, diabetes status and sex has been developed for the identification of cirrhosis in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). We assessed the performance of Agile-4 for ruling-in/out liver cirrhosis in MASLD patients.

We searched Medline, Cochrane library, Web of science, Scopus and Echosens website up to May 2024. Eligible studies assessed the accuracy of Agile-4 for ruling-in (≥0.565) and ruling-out (<0.251) liver cirrhosis, using biopsy as the reference standard, at predefined thresholds. We calculated pooled sensitivity and specificity estimates for both Agile-4 thresholds alongside 95% confidence intervals following bivariate random-effect models. We assessed the risk of bias using Quality Assessment of Diagnostic Accuracy Studies-2 tool.

We included seven studies with 6037 participants. An Agile-4 score ≥0.565 yielded a pooled specificity of 0.93 (95% CI, 0.86-0.97). Similarly, an Agile-4 score <0.251 excluded cirrhosis with a summary sensitivity of 0.90 (0.80-0.95). Assuming a cirrhosis prevalence of 30%, the positive predictive value (PPV) for ruling-in cirrhosis was 80%, while the negative predictive value for ruling-out cirrhosis was 95%. Most studies were at high or unclear risk for bias due to concerns regarding patient selection and the blinding status of Agile-4 score interpretation in relation to biopsy results.

Agile-4 score performs well for ruling-in/out liver cirrhosis in MASLD patients. Owing to the relatively low PPV, sequential application of the Agile-4 after fibrosis-4 index (FIB-4) testing might further enhance its performance.

This study aims to investigate the interobserver variability in the quantitative assessment of liver fat content using ultrasound attenuation imaging technology (USAT).

This prospective, single-center study included 96 adult patients who were either diagnosed with or suspected of having metabolic dysfunction-associated steatotic liver disease. Independent observers, blinded to each other's assessments, evaluated hepatic steatosis visually and through USAT measurements. Separate measurements were taken at five intercostal and subcostal sites, and the median values of these measurements were recorded. The correlation between USAT measurements and visual steatosis grades was examined using Spearman's correlation test. Intraclass correlation coefficient (ICC) and Bland-Altman analysis were used to evaluate the interobserver variability of USAT measurements.

Interobserver agreement for USAT measurements was excellent for the intercostal examination and good for the subcostal examination (p < 0.001). Body mass index did not significantly affect the level of interobserver agreement. Interobserver variability in Bland-Altman plots of USAT measurements was within the 95% limits of agreement. USAT measurements correlated very strongly with the visual degree of hepatic steatosis, both intercostal and subcostal (p < 0.001). USAT measurements were also significantly different between different visual degrees of hepatic steatosis (p < 0.001).

In the assessment of hepatic steatosis, USAT measurements obtained from the intercostal space showed excellent agreement in terms of interobserver reproducibility.

After hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer. Timely and accurate identification of ICC histological grade is critical for guiding clinical diagnosis and treatment planning.

We proposed a dual-branch deep neural network (SiameseNet) based on multiple-instance learning and cross-attention mechanisms to address tumor heterogeneity in ICC histological grade prediction. The study included 424 ICC patients (381 in training, 43 in testing). The model integrated imaging data from two modalities through cross-attention, optimizing feature representation for grade classification.

In the testing cohort, the model achieved an accuracy of 86.0%, AUC of 86.2%, sensitivity of 84.6%, and specificity of 86.7%, demonstrating robust predictive performance.

The proposed framework effectively mitigates performance degradation caused by tumor heterogeneity. Its high accuracy and generalizability suggest potential clinical utility in assisting histopathological assessment and personalized treatment planning for ICC patients.

Non-alcoholic fatty liver disease (NAFLD) is a spectrum of chronic liver diseases characterized by hepatic steatosis exceeding 5% in the absence of alcohol and other liver-damaging factors. Clinical studies have identified a potential link between abnormal iron metabolism and the high incidence of NAFLD; however, the results from clinical trials remain inconsistent. This meta-analysis aims to compare serum hepcidin levels and the hepcidin/ferritin ratio between adults with NAFLD and those without to explore their potential relationship with NAFLD.

A systematic search was conducted across the Web of Science platform, Cochrane, Scopus, Embase, and PubMed databases from their inception until December 18, 2024. The analysis primarily focused on serum hepcidin levels and the hepcidin/ferritin ratio. Observational studies comparing serum hepcidin levels and the hepcidin/ferritin ratio between individuals with NAFLD and control groups were included. A random-effects model was employed to calculate effect estimates, and outcomes were reported as standardized mean differences (SMD) with 95% confidence intervals (95% CI).

Following the systematic review, a total of 19 studies, comprising 2216 patients and 2125 controls, were included. The findings revealed a statistically significant difference in both hepcidin levels (SMD = 1.03, 95% CI: 0.49 to 1.56, p < 0.001) and the hepcidin/ferritin ratio (SMD = -1.13, 95% CI: -1.79 to -0.46, p < 0.001) between NAFLD and controls. Significant heterogeneity was observed across studies for both hepcidin (I² = 98.2%) and the hepcidin/ferritin ratio (I² = 93.3%), and the limited number of studies on hepcidin/ferritin were acknowledged as key limitations. Subgroup analysis revealed that patients with obesity exhibited higher levels of hepcidin (SMD = 1.12, 95% CI: 0.40 to 1.97) than overweight (SMD = 0.88, 95% CI: 0.05 to 1.72). Meta-regression analysis identified the hepcidin measurement method (p < 0.01), male-to-female ratio (p < 0.01), and study quality (p < 0.01) as significant moderators of the observed heterogeneity.

This meta-analysis revealed a significant association between hepcidin levels, the hepcidin/ferritin ratio and NAFLD in adults. Further investigations are needed to fully elucidate the role of these variables in iron metabolism and their potential impact on the diagnosis, prevention, and management of NAFLD.

The cancer metastatic cascade includes a series of mechanical barrier-crossing events, involving the physical movement of cancer cells from their primary location to a distant organ. This review describes the physical changes that influence tumour proliferation, progression, and metastasis. We identify potential mechanical signatures at every step of the metastatic cascade and discuss some latest mechanobiology-based therapeutic interventions to highlight the importance of interdisciplinary approaches in cancer diagnosis and treatment.

Liver fibrosis staging is challenging in patients with obesity and metabolic dysfunction-associated steatotic liver disease (MASLD). Liver biopsies are invasive, whereas noninvasive tests such as vibration-controlled transient elastography (VCTE) can be inaccurate in patients with obesity. We hypothesized that EUS-guided shear wave elastography (EUS-SWE) is more accurate for liver fibrosis staging in patients with MASLD and obesity; the aim of this pilot study was to test this hypothesis and establish optimal fibrosis stage cutoffs for EUS-SWE.

This was a multicenter, cross-sectional study from prospectively collected data. Consecutive patients who underwent EUS-SWE with subsequent liver biopsy were included. EUS-SWE was compared with Fibrosis-4 Index (FIB-4) and VCTE. Area under the receiver-operating characteristic (AUROC) curve analysis was performed, and 90% sensitivity and specific cutoffs were calculated to determine optimal cutoffs.

Sixty-two patients were included. Mean body mass index was 40.74 kg/m2. EUS-SWE was superior to FIB-4 in discriminating significant fibrosis (F2; AUROC, .87 vs .61; P < .0048) and advanced fibrosis (F3; AUROC, .93 vs .63; P < .0001), but not cirrhosis (F4; AUROC, .95 vs .81; P = .099). EUS-SWE was superior to VCTE in predicting advanced fibrosis and cirrhosis (P = .0067 and P = .0022, respectively). The 90% sensitivity cutoffs for EUS-SWE were 7.50, 8.48, and 11.30 for F2, F3, and F4, and the 90% specificity cutoffs were 9.82, 10.20, and 14.60.

In this pilot study, EUS-SWE was superior to FIB-4 and VCTE for liver fibrosis staging in patients with MASLD and obesity. (Clinical trial registration number: NCT05728697.).

Metabolic dysfunction-associated steatotic liver disease (MASLD) is an asymptomatic, multifaceted condition often associated with various risk factors, including fatigue, obesity, insulin resistance, metabolic syndrome, and sleep apnea. The increasing burden of MASLD underscores the critical need for early diagnosis and effective therapies. Owing to the lack of efficient therapies for MASLD, early diagnosis is crucial. Consequently, noninvasive biomarkers and imaging techniques are essential for analyzing disease risk and play a pivotal role in the global diagnostic process. The use of extracellular vesicles has emerged as promising for early diagnosis and therapy of various liver ailments. Herein, a comprehensive summary of the current diagnostic modalities for MASLD is presented, highlighting their advantages and limitations while exploring the potential of extracellular vesicles (EVs) as innovative diagnostic and therapeutic tools for MASLD. With this aim, this review emphasizes an in-depth understanding of the origin of EVs and the pathophysiological alterations of these ectosomes and exosomes in various liver diseases. This review also explores the therapeutic potential of EVs as key components in the future management of liver disease. The dual role of EVs as biomarkers and their therapeutic utility in MASLD essentially highlights their clinical integration to improve MASLD diagnosis and treatment. While EV-based therapies are still in their early stages of development and require substantial research to increase their therapeutic value before they can be used clinically, the diagnostic application of EVs has been extensively explored. Moving forward, developing diagnostic devices leveraging EVs will be crucial in advancing MASLD diagnosis. Thus, the literature summarized provides suitable grounds for clinicians and researchers to explore EVs for devising diagnostic and treatment strategies for MASLD.

To explore the connection between metabolic parameters and the severity of hepatic steatosis determined through ultrasound in elderly individuals with metabolic dysfunction-associated fatty liver disease (MAFLD).

4,663 senior individuals who were 65 years of age or older were included in this research. They were examined physically at the Ninghai Street Community Health Service Center in Yantai City between June 7, 2021, and October 15, 2021. There were two categories of individuals identified: the MAFLD group (n = 2,985) and the non-MAFLD group (n = 1,678). Based on liver ultrasonography results, individuals in the MAFLD group were further separated into three groups: mild (n = 2,104), moderate (n = 766), and severe (n = 115). To identify indicators of risk for the severity of hepatic steatosis, metabolic data was contrasted between the groups employing logistic regression.

In comparison to the non-MAFLD group, the MAFLD group showed significantly elevated levels of body mass index (BMI), blood pressure, gender, age, lipid profile, alanine transaminase (ALT), and fasting blood glucose (FBG; p < 0.05). Among individuals with MAFLD, there was a positive correlation between BMI, FBG, ALT, and aspartate transaminase (AST) levels and the severity of hepatic steatosis (p < 0.05). Logistic regression analysis indicated that BMI, female gender, FBG, ALT, triglycerides (TG), and serum uric acid (SUA) constituted risk factors for increased severity of hepatic steatosis in MAFLD.

The severity of hepatic steatosis in elderly MAFLD patients is significantly correlated with female gender, BMI, ALT, FBG, TG, and SUA.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver disease and is projected to become the leading indication for liver transplant (LT) in the US. Understanding its clinical burden can help to identify opportunities for prevention and treatment.

To project the burden of MASLD in US adults from 2020 to 2050.

This decision analytical modeling study used an agent-based state transition model that simulates the natural history of MASLD progression among adults 18 years of age or older. Primary data sources for model inputs were the published literature.

Natural history of MASLD.

Cases of MASLD, metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, hepatocellular carcinoma (HCC), LT, and liver-related death.

The model simulated 2 821 624 individuals (mean age. 35.8 years; 50.9% female). The model predicted a steady increase in the prevalence of MASLD from 33.7% (86.3 million people) in 2020 to 41.4% (121.9 million people) by 2050. Cases of MASH would increase from 14.9 million (5.8% of US adults) in 2020 to 23.2 million (7.9% of US adults) by 2050. The number of cases of MASH and clinically significant fibrosis (ie, F≥F2, centrilobular and periportal fibrosis or more severe disease) were estimated to increase from 6.7 million to 11.7 million. By 2046 to 2050, MASLD would cause 22 440 new cases of HCC and 6720 new cases of LT per year compared with 11 483 new cases of HCC and 1717 new cases of LT in 2020 to 2025. Liver-related mortality was estimated to increase from 30 500 deaths (1.0% of all-cause deaths in adults) in 2020 to 95 300 deaths (2.4%) in 2050.

In this decision analytical modeling study, the model forecast a substantial increase in clinical burden of MASLD over the next 3 decades in the absence of effective treatments. These results suggest that health systems should plan for large increases in the number of HCC cases and in the need for LT.

This study aimed to determine the burden of suspected nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) in a predominantly Hispanic patient population and explore the utility of the American Gastroenterological Association's NAFLD Clinical Care Pathway (CCP).

Electronic medical records (n = 223) were used to divide patients into risk groups based on the amount of metabolic risk factors they presented, diabetic status, or if they presented other liver diseases. Fribosis-4 (FIB-4) scores were used to determine the risk for advanced fibrosis.

Most patients (83.8%) were considered at risk for NAFLD based on CCP criteria, and about a third of patients (33.2%) were found to be at indeterminate (n = 60; 26.9%) or high risk (n = 14; 6.3%) for advanced fibrosis. Most indeterminate-risk patients (78.3%) were not referred for liver imaging.

This study demonstrates the potential of the CCP as a corrective tool that could help to better identify and screen patients at risk for NAFLD.

The early diagnosis of liver injury and in situ real-time monitoring of tumor therapy efficacy are important for the enhancement of personalized precision therapy but remain challenging due to the lack of reliable in vivo visualization tools with integrated diagnostic, therapeutic, and efficacy monitoring functions. Herein, a smart second near-infrared window (NIR-II) molecule (BITX-OH) is rationally designed for diagnosis and therapy by vinyl-bridging hydroxyl diphenyl xanthine unit and benzo[cd]indolium skeleton. BITX-OH exhibits high selectivity and sensitivity toward viscosity, exhibiting a significant enhancement (1167-fold) in NIR-II fluorescence at 962 nm. With the assistance of BITX-OH and NIR-II fluorescence imaging, early diagnosis and therapeutic evaluation of non-alcoholic fatty liver (NAFL), as well as in-site real-time monitoring of hepatic fibrosis (HF) in live mice have been successfully achieved, which is at least several hours earlier than the typical clinical test. Notably, BITX-OH displays excellent photothermal conversion efficiency when exposed to an 808 nm laser, which can induce tumor ablation and increase viscosity, thereby enhancing NIR-II fluorescence for the real-time evaluation of photothermal therapy (PTT). This viscosity-based "self-monitoring" strategy provides a convenient and reliable platform for timely obtaining therapeutic feedback to avoid over- or under-treatment, thus enabling personalized precision therapy.

The aim of this study was to compare the diagnostic performance of attenuation imaging (ATI), shear wave elastography (SWE), and shear wave dispersion (SWD) for detecting and grading hepatic steatosis in patients with metabolic dysfunction associated steatotic liver disease (MASLD).

Sixty-six patients with MASLD confirmed histopathologically and 34 healthy volunteers who were age/sex-matched were prospectively enrolled in this study. ATI, SWE, and SWD examinations were performed. Fibrosis stage, necroinflammatory activity, and steatosis grade were confirmed histopathologically. Steatosis was graded as follows: S0 (<5%); S1 (5%-32%); S2 (33%-66%) to S3 (>66%). We compared the diagnostic performance of ATI, SWE, and SWD for detecting and grading hepatic steatosis.

Both attenuation coefficient (AC) and SWD values were significantly different among the different hepatic steatosis, and both were correlated with hepatic steatosis. ATI had better diagnostic performance than SWD for detecting and grading hepatic steatosis. The area under the receiver operating characteristic (ROC) curve of ATI for detecting ≥S1, ≥S2, and =S3 were 0.917 (cut-off value of 0.69 dB/cm/MHz), 0.933 (cut-off value of 0.74 dB/cm/MHz), and 0.870 (cut-off value of 0.82 dB/cm/MHz), respectively. The area under the ROC curve of SWD value was 0.758 (cut-off value of 10.79 m/s/kHz), 0.685 (cut-off value of 12.64 m/s/kHz), and 0.722 (cut-off value of 13.24 m/s/kHz), respectively.

ATI technology is a reliable method for detecting and grading hepatic steatosis in patients with MASLD than SWE and SWD.

We compared the diagnostic performance of ATI, SWE, SWD for detecting and grading hepatic steatosis in patients with MASLD in order to find the best diagnostic parameters.

Integrating biomarkers into a comprehensive strategy is crucial for precise patient management, especially considering the significant healthcare costs associated with diseases. Current studies emphasize the urgent need for a paradigm shift in conceptualizing nonalcoholic fatty liver disease (NAFLD), now renamed metabolic dysfunction-associated steatotic liver disease (MASLD). Biomarkers are emerging as indispensable tools for accurate diagnosis, risk stratification, and monitoring disease progression. This review classifies biomarkers into conventional and novel categories, such as lipids, insulin resistance, hepatic function, and cutting-edge imaging/omics, and evaluates their potential to transform the approach to MASLD among individuals with type 2 diabetes mellitus (T2D). It focuses on the critical role of biomarkers in early MASLD detection, enhancing predictive accuracy, and discerning responses to interventions (pharmacological or lifestyle modifications). Amid this discussion, the complexities of the relationship between T2D and MASLD are explored, considering factors like age, gender, genetics, ethnicity, and socioeconomic background. Biomarkers enhance the effectiveness of interventions and support global initiatives to reduce the burden of MASLD, thereby improving public health outcomes. This review recognizes the promising potential of biomarkers for diagnostic precision while candidly addressing the challenges in implementing these advancements in clinical practice. The transformative role of biomarkers emerges as a central theme, promising to reshape our understanding of disease trajectories, prognosis, and the customization of personalized therapeutic strategies for improved patient outcomes. From a future perspective, identifying early-stage biomarkers, understanding environmental impact through exposomes, and applying a multiomics approach may reveal additional insight into MASLD development.

As people with human immunodeficiency virus experience longer life expectancy, other causes of morbidity and mortality are being increasingly identified. The incidence of non-alcoholic fatty liver disease has recently been on the rise in Indonesia. People with human immunodeficiency virus on antiretroviral therapy are also at an increased risk of having non-alcoholic fatty liver disease. The study aimed to define the prevalence and factors associated with non-alcoholic fatty liver disease in people with human immunodeficiency virus on stable antiretroviral therapy.

A cross-sectional study of people with human immunodeficiency virus, on antiretroviral therapy, age younger than 18 years old, and without hepatitis co-infection was conducted at the human immunodeficiency virus Integrated Clinic Cipto Mangunkusumo Hospital, Jakarta, Indonesia. Non-alcoholic fatty liver disease was diagnosed using transient elastography with associated controlled attenuation parameter examination (diagnostic cutoff: 238 db/m). A logistic regression test with Poisson regression was used to evaluate factors associated with non-alcoholic fatty liver disease.

One hundred and five people with human immunodeficiency virus were included, with a median age of 39 years and 65.7% were men. The prevalence of non-alcoholic fatty liver disease was 52.4%. Factors related to non-alcoholic fatty liver disease were hypertension (aPR: 1.49, 95% CI: 1.03-2.14, p = 0.033) and triglyceride levels (aPR: 1.001, 95% CI: 1.000-1.002, p = 0.024). No human immunodeficiency virus-specific variables were associated with non-alcoholic fatty liver disease.

More than half of Indonesian people with human immunodeficiency virus on antiretroviral therapy in this study were found to have non-alcoholic fatty liver disease. Hypertension and increased triglyceride levels were related to non-alcoholic fatty liver disease. Screening for non-alcoholic fatty liver disease should be implemented as a means of early intervention and to prevent complications.

The mechanisms underlying the association of steatotic liver disease with cardiovascular and cancer outcomes are poorly understood. We aimed to use MRI-derived measures of liver fat and genetics to investigate causal mechanisms that link higher liver fat to various health outcomes.

We conducted a genome-wide association study on 37,358 UK Biobank participants to identify genetic variants associated with liver fat measured from MRI scans. We used a Mendelian randomisation approach to investigate the causal effect of liver fat on health outcomes independent of BMI, alcohol consumption and lipids using data from published genome-wide association studies and FinnGen.

We identified 13 genetic variants associated with liver fat that had differing effects on the risks of health outcomes. Genetic variants associated with impaired hepatic triglyceride export showed liver fat-increasing alleles to be correlated with a reduced risk of coronary artery disease and myocardial infarction but an elevated risk of type 2 diabetes, while variants associated with enhanced de novo lipogenesis showed liver fat-increasing alleles to be linked to a higher risk of myocardial infarction and coronary artery disease. Genetically higher liver fat content increased the risk of non-alcohol-related cirrhosis, hepatocellular carcinoma, and intrahepatic bile duct and gallbladder cancers, exhibiting a dose-dependent relationship, irrespective of the mechanism.

This study provides fresh insight into the heterogeneous effect of liver fat on health outcomes. It challenges the notion that liver fat per se is an independent risk factor for cardiovascular disease, underscoring the dependency of this association on the specific mechanisms that drive fat accumulation in the liver. However, excess liver fat, regardless of the underlying mechanism, appears to be causally linked to cirrhosis and cancers in a dose-dependent manner.

This research advances our understanding of the heterogeneity in mechanisms influencing liver fat accumulation, providing new insights into how liver fat accumulation may impact various health outcomes. The findings challenge the notion that liver fat is an independent risk factor for cardiovascular disease and highlight the mechanistic effect of some genetic variants on fat accumulation and the development of cardiovascular diseases. This study is of particular importance for healthcare professionals including physicians and researchers, as well as patients, as it allows for more targeted and personalised treatment by understanding the relationship between liver fat and various health outcomes. The findings emphasise the need for a personalised management approach and a reshaping of risk assessment criteria. It also provides room for prioritising a clinical intervention aimed at reducing liver fat content (likely via intentional weight loss) that could help protect against liver-related fibrosis and cancer.

This study aims to validate the efficacy of the conventional non-invasive score in predicting significant fibrosis in metabolic-associated fatty liver disease (MAFLD) and to develop a non-invasive prediction model for MAFLD.

This cross-sectional study was conducted among 7701 participants with MAFLD from August 2018 to December 2023. All participants were divided into a training cohort and a validation cohort. The study compared different subgroups' demographic, anthropometric, and laboratory examination indicators and conducted logistic regression analysis to assess the correlation between independent variables and liver fibrosis. Nomograms were created using the logistic regression model. The predictive values of noninvasive models and nomograms were evaluated using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA).

Four nomograms were developed for the quantitative analysis of significant liver fibrosis risk based on the multivariate logistic regression analysis results. The nomogram's area under ROC curves (AUC) was 0.710, 0.714, 0.748, and 0.715 in overall MAFLD, OW-MAFLD, Lean-MAFLD, and T2DM-MAFLD, respectively. The nomogram had a higher AUC in all MAFLD participants and OW-MAFLD than the other non-invasive scores. The DCA curve showed that the net benefit of each nomogram was higher than that of APRI and FIB-4. In the validation cohort, the AUCs of the nomograms were 0.722, 0.750, 0.719, and 0.705, respectively.

APRI, FIB-4, and NFS performed poorly predicting significant fibrosis in patients with MAFLD. The new model demonstrated improved diagnostic accuracy and clinical applicability in identifying significant fibrosis in MAFLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD) comprises simple steatosis (SS), which has a low risk of mortality, and metabolic dysfunction-associated steatohepatitis (MASH), which can progress to liver cirrhosis and hepatocellular carcinoma. Because differentiation between MASH and SS is the most important issue in the diagnosis of MASLD, the establishment of noninvasive diagnostic methods is urgently needed. In this study, we evaluated the potential of [123I]IIMU, a thymidine phosphorylase (TYMP) targeted SPECT imaging probe, for differential diagnosis of MASLD in a preclinical animal model.

SS and MASH mice were prepared by feeding db/db mice with a standard diet and a methionine/choline-deficient diet, respectively. Control mice were prepared by feeding m/m mice with a standard diet. TYMP expression in the liver was evaluated by RT-PCR, western blotting, and immunohistochemistry. The biodistribution of [125I]IIMU in the three model mice was evaluated at 30 min post-injection. SPECT/CT imaging studies of the three model mice were performed 30 min after injection of [123I]IIMU.

Hepatic TYMP expression level was the highest in the SS mice and the lowest in the MASH mice at both mRNA and protein levels. The immunohistochemistry experiment showed a patchy distribution of TYMP only in the liver of MASH mice. In the biodistribution study, the hepatic accumulation of [125I]IIMU was the highest in the SS mice and the lowest in the MASH mice. The SPECT/CT imaging study showed similar results to the biodistribution experiment.

Hepatic TYMP expression level may serve as a promising imaging biomarker for differential diagnosis of SS and MASH. SPECT imaging using [123I]IIMU potentially provides a novel noninvasive diagnostic method to differentiate MASH and SS.

Non-invasive diagnostics for metabolic dysfunction-associated fatty liver disease (MAFLD) remain challenging. We aimed to identify novel key genes as non-invasive biomarkers for MAFLD, elucidate causal relationships between biomarkers and MAFLD and determine the role of immune cells as potential mediators.

Utilizing published transcriptome data of patients with biopsy-proven MAFLD, we applied linear models for microarray data, least absolute shrinkage and selector operation (LASSO) regressions and receiver operating characteristic (ROC) curve analyses to identify and validate biomarkers for MAFLD. Using the expression quantitative trait loci database and a cohort of 778 614 Europeans, we used Mendelian randomization to analyse the causal relationships between key biomarkers and MAFLD. Additionally, mediation analysis was performed to examine the involvement of 731 immunophenotypes in these relationships.

We identified 31 differentially expressed genes, and LASSO regression showed three hub genes, IGFBP2, PEG10, and P4HA1, with area under the receiver operating characteristic (AUROC) curve of 0.807, 0.772 and 0.791, respectively, for identifying MAFLD. The model of these three genes had an AUROC of 0.959 and 0.800 in the development and validation data sets, respectively. This model was also validated using serum-based enzyme-linked immunosorbent assay data from MAFLD patients and control subjects (AUROC: 0.819, 95% confidence interval: 0.736-0.902). PEG10 was associated with an increased MAFLD risk (odds ratio = 1.106, p = 0.032) via inverse variance-weighted analysis, and about 30% of this risk was mediated by the percentage of CD11c + CD62L- monocytes.

The MAFLD panels have good diagnostic accuracy, and the causal link between PEG10 and MAFLD was mediated by the percentage of CD11c + CD62L- monocytes.

Metabolic disturbances are major contributors to the onset and progression of non-alcoholic fatty liver disease (NAFLD), which includes a histological spectrum ranging from single steatosis (SS) to non-alcoholic steatohepatitis (NASH). This study aimed to identify serum metabolites and lipids enriched in different histological stages of NAFLD and to explore metabolites/lipids as non-invasive biomarkers in risk prediction of NAFLD and NASH in obese Chinese.

Serum samples and liver biopsies were obtained from 250 NAFLD subjects. Untargeted metabolomic and lipidomic profiling were performed using Liquid Chromatography-Mass Spectrometry. Significantly altered metabolites and lipids were identified by MaAsLin2. Pathway enrichment was conducted with MetaboAnalyst and LIPEA. WGCNA was implemented to construct the co-expression network. Logistic regression models were developed to classify different histological stages of NAFLD.

A total of 263 metabolites and 550 lipid species were detected in serum samples. Differential analysis and pathway enrichment analysis revealed the progressive patterns in metabolic mechanisms during the transition from normal liver to SS and to NASH, including N-palmitoyltaurine, tridecylic acid, and branched-chain amino acid signaling pathways. The co-expression network showed a distinct correlation between different triglyceride and phosphatidylcholine species with disease severity. Multiple models classifying NAFLD versus normal liver and NASH versus SS identified important metabolic features associated with significant improvement in disease prediction compared to conventional clinical parameters.

Different histological stages of NAFLD are enriched with distinct sets of metabolites, lipids, and metabolic pathways. Integrated algorithms highlight the important metabolic and lipidomic features for diagnosis and staging of NAFLD in obese individuals.

Advanced liver fibrosis is a critical stage in the evaluation of chronic liver disease (CLD), holding clinical significance in the development of treatment strategies and estimating the disease progression.

This paper proposes an innovative Global-Local Cross-View Network (GLCV-Net) for the automatic diagnosis of advanced liver fibrosis from ultrasound (US) B-mode images. The proposed method consists of three main components: 1. A Segmentation-enhanced Global Hybrid Feature Extractor for segmenting the liver parenchyma and extracting global features; 2. A Heatmap-weighted Local Feature Extractor for selecting candidate regions and automatically identifying suspicious areas to construct local features; 3. A Scale-adaptive Fusion Module to balance the contributions of global and local scales in evaluating advanced liver fibrosis.

The predictive performance of the model was validated on an internal dataset of 1003 chronic liver disease (CLD) patients and an external dataset of 46 CLD patients, both subjected to liver fibrosis staging through pathological assessment. On the internal dataset, GLCV-Net achieved 86.9% accuracy, 85.0% recall, 85.4% precision, and 85.2% F1-score. Further validation on the external dataset confirmed its robustness, with scores of 86.1% in accuracy, 83.1% in recall, 80.8% in precision, and 81.9% in F1-score.

These results underscore the GLCV-Net's potential as a promising approach for non-invasively and accurately diagnosing advanced liver fibrosis in CLD patients, breaking through the limitations of traditional methods by integrating global and local information of liver fibrosis, significantly enhancing diagnostic accuracy.

Increased prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) highlights a desire for screening with liver ultrasound normalized local variance (NLV). We aimed to assess variations in NLV values measured at different sampling depths and discuss common technical considerations in measuring liver NLV.

We retrospectively measured liver NLVs at variable depths on ultrasound images pre-recorded in 116 participants who underwent liver magnetic resonance imaging-proton density fat fraction (MRI-PDFF) and ultrasound to screen for MASLD. Liver NLVs were measured and differences at variable depths were tested using one-way analysis of variance (ANOVA) and multiple paired comparisons using post hoc Tukey honestly significant difference (HSD), Scheffé, Bonferroni, and Holm multiple comparisons. Diagnostic performance of NLV values were analyzed by area under the receiver operating characteristic (AUROC) curve.

The NLV measured at a depth of 10 cm significantly differed from those measured near the liver capsule and at depths of 6 cm and 8 cm (p < 0.001) from the skin. There was no significant difference in NLV value in other paired groups (p > 0.05). The difference in the area under AUROCs for NLVs measured at variable depths was not significant (p > 0.05).

The best diagnostic performance of liver NLV was measured at depth of 8 cm from the skin, although NLV measured at variable depth showed similar diagnostic performance for assessing ≥ mild hepatic steatosis. The study results provide a reference that can be used in the development of standardized scanning protocols and technical considerations in measuring liver NLV.

Liver fibrosis is a common pathway shared by all forms of progressive chronic liver disease. There is an unmet clinical need for noninvasive imaging tools to diagnose and stage fibrosis, which presently relies heavily on percutaneous liver biopsy. Here we explored the feasibility of using a novel type I collagen-targeted manganese (Mn)-based MRI probe, Mn-CBP20, for liver fibrosis imaging. In vitro characterization of Mn-CBP20 demonstrated its high binding affinity for human collagen (K d = 9.6 μM), high T1-relaxivity (48.9 mM-1s-1 at 1.4T and 27°C), and kinetic inertness to Mn release under forcing conditions. We demonstrated MRI using Mn-CBP20 performs comparably to previously reported gadolinium-based type I collagen-targeted probe EP-3533 in a mouse model of carbon tetrachloride-induced liver fibrosis, and further demonstrate efficacy to detect fibrosis in a diet-induced mouse model of metabolically-associated steatohepatitis. Biodistribution studies using the Mn-CBP20 radio-labeled with the positron-emitting 52Mn isotope demonstrate efficient clearance of Mn-CBP20 primarily via renal excretion. Mn-CBP20 represents a promising candidate that merits further evaluation and development for molecular imaging of liver fibrosis.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing public health concern worldwide. Liver biopsy is the gold standard for diagnosing and staging MASLD, but it is invasive and carries associated risks. In recent years, there has been significant progress in developing noninvasive techniques for evaluation. This review article discusses briefly current available noninvasive assessments and the various liver biopsy techniques available for MASLD, including invasive techniques such as transjugular and transcutaneous needle biopsy, intraoperative/laparoscopic biopsy, and the evolving role of endoscopic ultrasound-guided biopsy. In addition to discussing the various biopsy techniques, we review the current state of knowledge on the histopathologic evaluation of MASLD, including the various scoring systems used to grade and stage the disease. We also explore current and alternative modalities for histopathologic evaluation, such as whole slide imaging and the utility of immunohistochemistry. Overall, this review article provides a comprehensive overview of the progress in liver biopsy techniques for MASLD and compares invasive and noninvasive modalities. However, beyond clinical trials, the practical application of liver biopsy may be limited, as ongoing advancements in noninvasive fibrosis assessments are expected to more effectively identify candidates for MASLD treatment in real-world settings.

The global incidence of nonalcoholic fatty liver disease (NAFLD) is escalating considerably. NAFLD covers a range of liver conditions from simple steatosis to the more severe form known as nonalcoholic steatohepatitis, which involves chronic liver inflammation and the transformation of hepatic stellate cells into myofibroblasts that generate excess extracellular matrix, leading to fibrosis. Hepatocyte ballooning is a key catalyst for fibrosis progression, potentially advancing to cirrhosis and its decompensated state. Fibrosis is a critical prognostic factor for outcomes in patients with NAFLD; therefore, those with substantial fibrosis require timely intervention. Although liver biopsy is the most reliable method for fibrosis detection, it is associated with certain risks and limitations, particularly in routine screening. Consequently, various noninvasive diagnostic techniques have been introduced. This review examines the increasing prevalence of NAFLD, evaluates the noninvasive diagnostic techniques for fibrosis, and assesses their efficacy in staging the disease. In addition, it critically appraises current and emerging antifibrotic therapies, focusing on their mechanisms, efficacy, and potential in reversing fibrosis. This review underscores the urgent need for effective therapeutic strategies, given the dire consequences of advanced fibrosis.

The global rise of chronic hepatitis B (CHB) superimposed on hepatic steatosis (HS) warrants noninvasive, precise tools for assessing fibrosis progression. This study leveraged machine learning (ML) to develop diagnostic models for advanced fibrosis and cirrhosis in this patient population.

Treatment-naive CHB patients with concurrent HS who underwent liver biopsy in 10 medical centers were enrolled as a training cohort and an independent external validation cohort (NCT05766449). Six ML models were implemented to predict advanced fibrosis and cirrhosis. The final models, derived from SHAP (Shapley Additive exPlanations), were compared with Fibrosis-4 Index, nonalcoholic fatty liver disease Fibrosis Score, and aspartate aminotransferase-to-platelet ratio index using the area under receiver-operating characteristic curve (AUROC) and decision curve analysis (DCA).

Of 1,198 eligible patients, the random forest model achieved AUROCs of 0.778 (95% confidence interval [CI], 0.749-0.807) for diagnosing advanced fibrosis (random forest advanced fibrosis model) and 0.777 (95% CI, 0.748-0.806) for diagnosing cirrhosis (random forest cirrhosis model) in the training cohort, and maintained high AUROCs in the validation cohort. In the training cohort, the random forest advanced fibrosis model obtained an AUROC of 0.825 (95% CI, 0.787-0.862) in patients with hepatitis B virus DNA ≥105 IU/mL, and the random forest cirrhosis model had an AUROC of 0.828 (95% CI, 0.774-0.883) in female patients. The 2 models outperformed Fibrosis-4 Index, nonalcoholic fatty liver disease Fibrosis Score, and aspartate aminotransferase-to-platelet ratio index in the training cohort, and also performed well in the validation cohort.

The random forest models provide reliable, noninvasive tools for identifying advanced fibrosis and cirrhosis in CHB patients with concurrent HS, offering a significant advancement in the comanagement of the 2 diseases.

gov, Number: NCT05766449.

Despite the widespread use of diffusion-weighted imaging (DWI) in metabolic dysfunction-associated fatty liver disease (MAFLD), MRI acquisition and quantification techniques vary in the literature suggesting the need for established and reproducible protocols. The goal of this study was to assess inter-visit and inter-reader reproducibility of DWI- and IVIM-derived parameters in patients with MAFLD and healthy volunteers using extensive sampling of the "fast" compartment, non-rigid registration, and exclusion voxels with poor fit quality.

From June 2019 to April 2023, 31 subjects (20 patients with biopsy-proven MAFLD and 11 healthy volunteers) were included in this IRB-approved study. Subjects underwent MRI examinations twice within 40 days. 3.0 T DWI was acquired using a respiratory-triggered spin-echo diffusion-weighted echo-planar imaging sequence (b-values of 0, 10, 20, 30, 40, 50, 100, 200, 400, 800 s/mm2). DWI series were co-registered prior to voxel-wise non-linear regression of the IVIM model and voxels with poor fit quality were excluded (normalized root mean squared error ≥ 0.05). IVIM parameters (perfusion fraction, f; diffusion coefficient, D; and pseudo-diffusion coefficient, D*), and apparent diffusion coefficients (ADC) were computed from manual segmentation of the right liver lobe performed by two analysts on two MRI examinations.

All results are reported for f, D, D*, and ADC respectively. For inter-reader agreement on the first visit, ICC were of 0.985, 0.994, 0.986, and 0.993 respectively. For intra-reader agreement of analyst 1 assessed on both imaging examinations, ICC between visits were of 0.805, 0.759, 0.511, and 0.850 respectively. For inter-reader agreement on the first visit, mean bias and 95 % limits of agreement were (0.00 ± 0.03), (-0.01 ± 0.03) × 10-3 mm2/s, (0.70 ± 10.40) × 10-3 mm2/s, and (-0.02 ± 0.04) × 10-3 mm2/s respectively. For intra-reader agreement of analyst 1, mean bias and 95 % limits of agreement were (0.01 ± 0.09) × 10-3 mm2/s, (-0.01 ± 0.21) × 10-3 mm2/s, (-13.37 ± 56.19) × 10-3 mm2/s, and (-0.01 ± 0.16) × 10-3 mm2/s respectively. Except for parameter D* that was associated with between-subjects parameter variability (P = 0.009), there was no significant variability between subjects, examinations, or readers.

With our approach, IVIM parameters f, D, D*, and ADC provided excellent inter-reader agreement and good to very good inter-visit or intra-reader agreement, thus showing the reproducibility of IVIM-DWI of the liver in MAFLD patients and volunteers.

Since its introduction in 1980, fatty liver disease (now termed metabolic dysfunction-associated steatotic liver disease [MASLD]) has grown in prevalence significantly, paralleling the rise of obesity worldwide. While MASLD has been the subject of extensive research leading to significant progress in the understanding of its pathophysiology and progression factors, several gaps in knowledge remain. In this pictorial review, the authors present the latest insights into MASLD, covering its recent nomenclature change, spectrum of disease, epidemiology, morbidity, and mortality. The authors also discuss current qualitative and quantitative imaging methods for assessing and monitoring MASLD. Last, they propose six unsolved challenges in MASLD assessment, which they term the proliferation, reproducibility, reporting, needle-in-the-haystack, availability, and knowledge problems. These challenges offer opportunities for the radiology community to proactively contribute to their resolution. The authors conclude with a call to action for the entire radiology community to claim a seat at the table, collaborate with other societies, and commit to advancing the development, validation, dissemination, and accessibility of the imaging technologies required to combat the looming health care crisis of MASLD.

Treatment strategies for preventing liver fibrosis have not yet been established. Letrozole, widely used for breast cancer, has recently been reported to suppress liver fibrosis in murine models. Therefore, we aimed to validate the suppressive effects of letrozole on liver fibrosis in the clinical setting. From 2006 to 2020, 23 consecutive patients who received continuous letrozole treatment for 24 months or more and had a liver fibrosis marker FIB-4 index of ≥ 2.30, were included. Forty-three patients who underwent anastrozole treatment for 24 months or more and had a liver fibrosis marker FIB-4 index of ≥ 2.30, were also included as controls. The Fisher exact, chi-square, unpaired Student t, and paired Student t test were used to analyze the data. The patient characteristics were similar between the letrozole- and anastrozole-treated patient groups. Among the letrozole-treated patients, the mean FIB-4 index tended to decline during letrozole treatment; a significant decrease was observed at 18 and 24 months compared with the baseline values (p = 0.044 and p = 0.013). In addition, the mean aspartate aminotransferase-to-platelet ratio index (APRI) decreased during letrozole treatment; the values at 18 and 24 months were significantly lower than those at baseline (p = 0.024 and p = 0.026). In contrast, among anastrozole-treated patients, the mean FIB-4 index and APRI did not change during anastrozole treatment. When changes in the FIB-4 index were further examined in a limited number of patients with a FIB-4 index ≥ 2.67, a significant reduction in the FIB-4 index at 24 months compared with baseline was also observed in letrozole-treated patients (p = 0.023), but not in anastrozole-treated patients. In conclusion, our findings support a possible suppressive effect of letrozole on liver fibrosis in the clinical setting. Further studies are required to better understand the pharmacological effects of letrozole.