Liver Proton Density Fat Fraction Research Articles

MRI Dixon Fat-Corrected Look-Locker T1 Mapping for Quantification of Liver Fibrosis and Inflammation—A Comparison With the Non–Fat-Corrected Shortened Modified Look-Locker Inversion Recovery Technique

Objectives This study evaluates the impact of liver steatosis on the discriminative ability for liver fibrosis and inflammation using a novel Dixon water-only fat-corrected Look-Locker T1 mapping sequence, compared with a standard shortened Modified Look-Locker Inversion Recovery (shMOLLI) sequence, with the aim of overcoming the limitation of steatosis-related confounding in liver T1 mapping. Materials and Methods 3 T magnetic resonance imaging of the liver including the 2 T1 mapping sequences and proton density fat fraction (PDFF) was prospectively performed in 24 healthy volunteers and 38 patients with histologically proven liver fibrosis evaluated within 90 days of liver biopsy. Paired Mann-Whitney test compared sequences between participants with and without significant liver steatosis (PDFF cutoff 10%), and unpaired Kruskal-Wallis test compared healthy volunteers to patients with early (F0–2) and advanced (F3–4) liver fibrosis, as well as low (A0–1) and marked (A2–3) inflammatory activity. Univariate and multivariate logistic regression models assessed the impact of liver steatosis on both sequences. Results Dixon_W T1 was higher than shMOLLI T1 in participants without steatosis (median 896 ms vs 890 ms, P = 0.04), but lower in participants with liver steatosis (median 891 ms vs 973 ms, P < 0.001). Both methods accurately differentiated between volunteers and patients with early and advanced fibrosis (Dixon_W 849 ms, 910 ms, 947 ms, P = 0.011; shMOLLI 836 ms, 918 ms, 978 ms, P < 0.001), and those with mild and marked inflammation (Dixon_W 849 ms, 896 ms, 941 ms, P < 0.01; shMOLLI 836 ms, 885 ms, 978 ms, P < 0.001). Univariate logistic regression showed slightly lower performance of the Dixon_W sequence in differentiating fibrosis (0.69 vs 0.73, P < 0.01), compensated by adding liver PDFF in the multivariate model (0.77 vs 0.75, P < 0.01). Conclusions Dixon water-only fat-corrected Look-Locker T1 mapping accurately identifies liver fibrosis and inflammation, with less dependency on liver steatosis than the widely adopted shMOLLI T1 mapping technique, which may improve its predictive value for these conditions.

Accelerated free-breathing liver fat and quantification using multi-echo stack-of-radial MRI with motion-resolved multidimensional regularized reconstruction: Initial retrospective evaluation.

To improve image quality, mitigate quantification biases and variations for free-breathing liver proton density fat fraction (PDFF) and quantification accelerated by radial k-space undersampling. A free-breathing multi-echo stack-of-radial MRI method was developed with compressed sensing with multidimensional regularization. It was validated in motion phantoms with reference acquisitions without motion and in 11 subjects (6 patients with nonalcoholic fatty liver disease) with reference breath-hold Cartesian acquisitions. Images, PDFF, and maps were reconstructed using different radial view k-space sampling factors and reconstruction settings. Results were compared with reference-standard results using Bland-Altman analysis. Using linear mixed-effects model fitting (p < 0.05 considered significant), mean and SD were evaluated for biases and variations of PDFF and , respectively, and coefficient of variation on the first echo image was evaluated as a surrogate for image quality. Using the empirically determined optimal sampling factor of 0.25 in the accelerated in vivo protocols, mean differences and limits of agreement for the proposed method were [-0.5; -33.6, 32.7] s-1 for and [-1.0%; -5.8%, 3.8%] for PDFF, close to those of a previous self-gating method using fully sampled radial views: [-0.1; -27.1, 27.0] s-1 for and [-0.4%; -4.5%, 3.7%] for PDFF. The proposed method had significantly lower coefficient of variation than other methods (p < 0.001). Effective acquisition time of 64 s or 59 s was achieved, compared with 171 s or 153 s for two baseline protocols with different radial views corresponding to sampling factor of 1.0. This proposed method may allow accelerated free-breathing liver PDFF and mapping with reduced biases and variations.

Effect of an Asian-adapted Mediterranean diet and pentadecanoic acid on fatty liver disease: the TANGO randomized controlled trial

BackgroundWeight loss is the most effective treatment for nonalcoholic fatty liver disease (NAFLD). There is evidence that the Mediterranean diets rich in unsaturated fatty acids and fiber have beneficial effects on weight homeostasis and metabolic risk factors in individuals with NAFLD. Studies have also shown that higher circulating concentrations of pentadecanoic acid (C15:0) are associated with a lower risk for NAFLD. ObjectivesTo examine the effects of a Mediterranean-like, culturally contextualized Asian diet rich in fiber and unsaturated fatty acids, with or without C15:0 supplementation, in Chinese females with NAFLD. MethodsIn a double-blinded, parallel-design, randomized controlled trial, 88 Chinese females with NAFLD were randomly assigned to 1 of the 3 groups for 12 wk: diet with C15:0 supplementation (n = 31), diet without C15:0 supplementation (n = 28), or control (habitual diet and no C15:0 supplementation, n = 29). At baseline and after the intervention, body fat percentage, intrahepatic lipid content, muscle and abdominal fat, liver enzymes, cardiometabolic risk factors, and gut microbiome were assessed. ResultsIn the intention-to-treat analysis, weight reductions of 4.0 ± 0.5 kg (5.3%), 3.4 ± 0.5 kg (4.5%), and 1.5 ± 0.5 kg (2.1%) were achieved in the diet-with-C15:0, diet without-C15:0, and the control groups, respectively. The proton density fat fraction (PDFF) of the liver decreased by 33%, 30%, and 10%, respectively. Both diet groups achieved significantly greater reductions in body weight, liver PDFF, total cholesterol, gamma-glutamyl transferase, and triglyceride concentrations compared with the control group. C15:0 supplementation reduced LDL-cholesterol further, and increased the abundance of Bifidobacterium adolescentis. Fat mass, visceral adipose tissue, subcutaneous abdominal adipose tissue (deep and superficial), insulin, glycated hemoglobin, and blood pressure decreased significantly in all groups, in parallel with weight loss. ConclusionMild weight loss induced by a Mediterranean-like diet adapted for Asians has multiple beneficial health effects in females with NAFLD. C15:0 supplementation lowers LDL-cholesterol and may cause beneficial shifts in the gut microbiome. Trial registration numberThis trial was registered at the clinicaltrials.gov as NCT05259475.

Genetically predicted plasma levels of amino acids and metabolic dysfunction-associated fatty liver disease risk: a Mendelian randomization study

BackgroundEmerging metabolomics-based studies suggested links between amino acid metabolism and metabolic dysfunction-associated fatty liver disease (MAFLD) risk; however, whether there exists an aetiological role of amino acid metabolism in MAFLD development remains unknown. The aim of the present study was to assess the causal relationship between circulating levels of amino acids and MAFLD risk.MethodsWe conducted a two-sample Mendelian randomization (MR) analysis using summary-level data from genome-wide association studies (GWAS) to evaluate the causal relationship between genetically predicted circulating levels of amino acids and the risk of MAFLD. In the discovery MR analysis, we used data from the largest MAFLD GWAS (8434 cases and 770,180 controls), while in the replication MR analysis, we used data from a GWAS on MAFLD (1483 cases and 17,781 controls) where MAFLD cases were diagnosed using liver biopsy. We used Wald ratios or inverse variance-weighted (IVW) methods in the MR main analysis and weighted median and MR-Egger regression analyses in sensitivity analyses. Furthermore, we performed a conservative MR analysis by restricting genetic instruments to those directly involved in amino acid metabolism pathways.ResultsWe found that genetically predicted higher alanine (OR = 1.43, 95% CI 1.13–1.81) and lower glutamine (OR = 0.83, 95% CI 0.73–0.96) levels were associated with a higher risk of developing MAFLD based on the results from the MR main and conservative analysis. The results from MR sensitivity analyses and complementary analysis using liver proton density fat fraction as a continuous outcome proxying for MAFLD supported the main findings.ConclusionsNovel causal metabolites related to MAFLD development were uncovered through MR analysis, suggesting future potential for evaluating these metabolites as targets for MAFLD prevention or treatment.

Associations between types and sources of dietary carbohydrates and liver fat: a UK Biobank study

Background and aimsExcess energy intake can lead to metabolic dysfunction-associated steatotic liver disease (MASLD), but the relationship between dietary carbohydrate intake and liver fat content remains unclear. This study aimed to examine the associations between types and sources of dietary carbohydrates and liver fat content.MethodsUK Biobank participants with no pre-existing diabetes, liver disease or cardiovascular disease reported dietary intake of types and sources of carbohydrates (total carbohydrates, free sugars, non-free sugars, starch from whole grains, starch from refined grains, and fibre) on at least two 24-h dietary assessments. In cross-sectional analyses, (n = 22,973), odds ratios (OR) of high liver fat content (defined as a score of ≥ 36 in the hepatic steatosis index) by quintiles of carbohydrate intakes were estimated using multivariable logistic regression models. In prospective analyses, a second sample (n = 9268) had liver proton density fat fraction (PDFF) measured by magnetic resonance imaging (2014–2020). Multivariable linear regression models estimated geometric means of PDFF (%) by quintiles of carbohydrate intakes. Models were adjusted for demographic and lifestyle confounders, including total energy intake.ResultsIn the cross-sectional analyses, 6894 cases of high liver fat content were identified. Inverse associations between intakes of fibre (OR of highest vs. lowest quintile 0.46 [95% CI: 0.41–0.52]), non-free sugars (0.63 [0.57–0.70]) and starch from whole grains (0.52 [0.47–0.57]) with liver fat were observed. There were positive associations between starch from refined grains and liver fat (1.33 [1.21–1.46]), but no association with free sugars (p=0.61). In prospective analyses, inverse associations with PDFF (%) were observed for intakes of fibre (− 0.48 geometric mean difference between highest and lowest quintile of intake [− 0.60 to − 0.35]), non-free sugars (− 0.37 [− 0.49 to − 0.25]) and starch from whole grains (− 0.31 [− 0.42 to − 0.19]). Free sugars, but not starch from refined grains, were positively associated with PDFF (0.17 [0.05 to 0.28]).ConclusionThis study suggests that different carbohydrate types and sources have varying associations with liver fat, which may be important for MASLD prevention. Non-free sugars, fibre, and starch from whole grains could be protective, while associations with free sugars and starch from refined grains are less clear.

Liver fibrosis is associated with left ventricular remodeling: insights into the liver-heart axis

Abstract Background Non-alcoholic fatty liver disease (NAFLD), common in type 2 diabetes, has emerged as an important and independent risk factor for adverse cardiac remodeling. Fibrosis in the liver could be a key factor in this relationship. Despite the fact that NAFLD is a long-term progressive disease, imaging studies on this topic are mainly limited to selected patients from tertiary centres. Purpose To investigate the relationship between liver fat, liver fibrosis and cardiac remodeling in the general population. We also sought to explore biomarkers of cardiovascular inflammation and fibrosis, for possible mechanistic pathways in these relationships. Methods We included 46 participants with type 2 diabetes and 46 age and sex-matched controls (overall 35%/65% F/M, mean age 59.5 ± 4.6), all randomly sampled from the general population. Participants underwent careful clinical phenotyping, including blood sampling, echocardiography, and magnetic resonance imaging (MRI) at 1.5 T. The MRI protocol included sequences for quantification of liver proton density fat fraction (spectroscopy), liver fibrosis (stiffness from elastography at 56 Hz), left ventricular (LV) structure, function, and tissue characteristics (native T1 mapping). We also analyzed ∼290 circulating cardiovascular biomarkers. A Bayesian statistical approach (‘Stochastic Search Variable Selection’) was used to identify the biomarkers most strongly associated with cardiac remodeling. Results For liver stiffness, the mean value was 2.1 ± 0.4 kPa and the highest value was 2.9 kPa. The median liver fat value was 5.7% (IQR 9.9%) and 53 participants (58%) displayed hepatic steatosis (liver fat &amp;gt; 5%). LV concentricity increased across quartiles of liver stiffness (P=0.0014 for ANOVA), while LV concentricity and diastolic dysfunction increased across quartiles of liver fat (P=0.0023 and P=0.030 for ANOVA, respectively). Myocardial T1 displayed no relationships to neither liver fat nor liver stiffness. In a multiple linear regression, liver stiffness was positively associated with LV concentricity (Beta=0.26, P=0.0053), independently of diabetes and liver fat. This association was attenuated (Beta=0.17, P=0.077) when adjusting for circulating levels of IL-1 receptor type 2, the biomarker with the strongest association to LV concentricity in the Bayesian statistical analysis. Conclusion In our well-characterized subjects from the general population, we found that a majority had hepatic steatosis but overall rather low liver stiffness values. Despite this, liver stiffness was related to increased LV concentricity independently of liver fat and diabetes. This association was attenuated when also adjusting for IL-1 receptor type 2. Our results suggest a link between liver fibrosis and cardiac remodeling also in the early stages of fatty liver disease, possibly involving the IL-1 signaling pathway. Future studies are needed to further establish causality and potential mechanisms.Multiple linear regression analysesLiver magnetic resonance elastogram

Correcting gradient chain induced fat quantification errors in radial multi-echo Dixon imaging using a gradient modulation transfer function

Purpose: Multi-echo Stack-of-stars (SoS) radial k-space trajectories with golden angle ordering are becoming popular for free-breathing abdominal Dixon imaging and proton density fat fraction (PDFF) mapping. Gradient chain imperfections including eddy currents and system delays are known to affect the image quality of radial imaging and to confound the estimation of PDFF mapping. This work proposes a retrospective trajectory correction method based on a simple gradient modulation transfer function (GMTF) measurement to predict and correct gradient chain induced k-space trajectory errors.Methods: The GMTF was measured using the standard hardware of a 3 Tesla scanner on a phantom using the thin slice method and was applied to a 3D radial SoS Dixon imaging sequence. The impact of the GMTF-based correction on image reconstruction and PDFF quantification was investigated using numerical simulations and validated on experimental phantom data as well as on in vivo leg and liver data of healthy volunteers.Results: Correcting the k-space trajectories with the measured GMTF during image reconstruction reduced PDFF quantification errors for phantom and in vivo acquisitions. A Bland-Altman comparison of the measured PDFF phantom and reference data confirmed that the GMTF correction narrowed down the limits of agreement (LoA) from 1.3% ± 8.1% (uncorrected) to 1.9% ± 5.4% (GMTF-corrected) over the full PDFF range (0%–100%) and from −0.26% ± 2.8% (uncorrected) to 0.12% ± 1.5% (GMTF-corrected) within the 0%–50% PDFF range. Liver PDFF estimation was improved by reducing the standard deviation of the mean liver PDFF and the bias of the mean liver PDFF for all subjects.Conclusion: The proposed GMTF-based k-space trajectory correction is a fast alternative method for avoiding PDFF quantitation errors caused by gradient-system induced k-space trajectory errors in 3D radial multi-echo gradient-echo acquisitions.

Quantitative ultrasound fatty liver evaluation in a pediatric population: comparison with magnetic resonance imaging of liver proton density fat fraction

BackgroundBiopsy remains the gold standard for the diagnosis of hepatic steatosis, the leading cause of pediatric chronic liver disease; however, its costs call for less invasive methods.ObjectiveThis study examined the diagnostic accuracy and reliability of quantitative ultrasound (QUS) for the assessment of liver fat content in a pediatric population, using magnetic resonance imaging proton density fat fraction (MRI-PDFF) as the reference standard.Materials and methodsWe enrolled 36 patients. MRI-PDFF involved a 3-dimensional T2*-weighted with Dixon pulse multiple-echo sequence using iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL IQ). QUS imaging relied on the ultrasound system “RS85 A” (Samsung Medison, Seoul, South Korea) and the following software: Hepato-Renal Index with automated region of interest recommendation (EzHRI), Tissue Attenuation Imaging (TAI), and Tissue Scatter Distribution Imaging (TSI). For each QUS index, receiver operating characteristic (ROC) curve analysis against MRI-PDFF was used to identify the associated cut-off value and the area under the ROC curve (AUROC). Concordance between two radiologists was assessed by intraclass correlation coefficients (ICCs) and Bland–Altman analysis.ResultsA total of 61.1% of the sample (n=22) displayed a MRI-PDFF ≥ 5.6%; QUS cut-off values were TAI=0.625 (AUROC 0.90, confidence interval [CI] 0.77–1.00), TSI=91.95 (AUROC 0.99, CI 0.98–1.00) and EzHRI=1.215 (AUROC 0.98, CI 0.94–1.00). Inter-rater reliability was good-to-excellent for EzHRI (ICC 0.91, 95% C.I. 0.82–0.95) and TAI (ICC 0.94, 95% C.I. 0.88–0.97) and moderate to good for TSI (ICC 0.73; 95% C.I. 0.53–0.85).ConclusionOur results suggest that QUS can be used to reliably assess the presence and degree of pediatric hepatic steatosis.Graphical abstract

Application of multi-echo Dixon and MRS in quantifying hepatic fat content and staging liver fibrosis

This study associated the liver proton density fat fraction (PDFF), measured by multi-echo Dixon (ME-Dixon) and breath-hold single-voxel high-speed T2-corrected multi-echo 1H magnetic resonance spectroscopy (HISTO) at 1.5 T, with serum biomarkers and liver fibrosis stages. This prospective study enrolled 75 patients suspected of liver fibrosis and scheduled for liver biopsy and 23 healthy participants with normal liver function. The participant underwent ME-Dixon and HISTO scanning. The agreement of PDFF measured by ME-Dixon (PDFF-D) and HISTO (PDFF-H) were compared. Correlations between PDFF and serum fat biomarkers (total cholesterol, triglyceride, and high- and low-density lipoproteins) and the liver fibrosis stages were assessed. PDFF were compared among the liver fibrosis stages (F0–F4) based on clinical liver biopsies. The Bland–Altman plot showed agreement between PDFF-D and PDFF-H(LoA, − 4.44 to 6.75), which have high consistency (ICC 0.752, P < 0.001). The correlations with the blood serum markers were mild to moderate (PDFF-H: r = 0.261–0.410, P < 0.01; PDFF-D: r = 0.265–0.367, P < 0.01). PDFF-D, PDFF-H, and steatosis were distributed similarly among the liver fibrosis stages. PDFF-H showed a slight negative correlation with the liver fibrosis stages (r = − 0.220, P = 0.04). Both ME-Dixon and HISTO sequences measured liver fat content noninvasively. Liver fat content was not directly associated with liver fibrosis stages.

Evaluation of proton density fat fraction (PDFF) obtained from a vendor-neutral MRI sequence and MRQuantif software.

To validate the proton density fat fraction (PDFF) obtained by the MRQuantif software from 2D chemical shift encoded MR (CSE-MR) data in comparison with the histological steatosis data. This study, pooling data from 3 prospective studies spread over time between January 2007 and July 2020, analyzed 445 patients who underwent 2D CSE-MR and liver biopsy. MR derived liver iron concentration (MR-LIC) and PDFF was calculated using the MRQuantif software. The histological standard steatosis score (SS) served as reference. In order to get a value more comparable to PDFF, histomorphometry fat fraction (HFF) were centrally determined for 281 patients. Spearman correlation and the Bland and Altman method were used for comparison. Strong correlations were found between PDFF and SS (rs = 0.84, p < 0.001) or HFF (rs = 0.87, p < 0.001). Spearman's coefficients increased to 0.88 (n = 324) and 0.94 (n = 202) when selecting only the patients without liver iron overload. The Bland and Altman analysis between PDFF and HFF found a mean bias of 5.4% ± 5.7 [95% CI 4.7, 6.1]. The mean bias was 4.7% ± 3.7 [95% CI 4.2, 5.3] and 7.1% ± 8.8 [95% CI 5.2, 9.0] for the patients without and with liver iron overload, respectively. The PDFF obtained by MRQuantif from a 2D CSE-MR sequence is highly correlated with the steatosis score and very close to the fat fraction estimated by histomorphometry. Liver iron overload reduced the performance of steatosis quantification and joint quantification is recommended. This device-independent method can be particularly useful for multicenter studies. The quantification of liver steatosis using a vendor-neutral 2D chemical-shift MR sequence, processed by MRQuantif, is well correlated to steatosis score and histomorphometric fat fraction obtained from biopsy, whatever the magnetic field and the MR device used. • The PDFF measured by MRQuantif from 2D CSE-MR sequence data is highly correlated to hepatic steatosis. • Steatosis quantification performance is reduced in case of significant hepatic iron overload. • This vendor-neutral method may allow consistent estimation of PDFF in multicenter studies.

1379-P: Adding Salt to Foods and Risk of Severe Nonalcoholic Fatty Liver

Background: High sodium intake is associated with insulin resistance, obesity, and metabolic syndrome, whereas very few studies have assessed the association of sodium intake with risk of nonalcoholic fatty liver disease (NAFLD). We recently found that the frequency of adding salt to foods could reflect a person’s long-term salt taste preference and sodium intake and was significantly related to life expectancy and cardiovascular disease risk. In this study, we aimed to evaluate the association between the frequency of adding salt to foods and liver proton density fat fraction (PDFF, a magnetic resonance imaging-based measure to assess liver fat content) and severe NAFLD risk. Methods: A total of 494,240 participants from UK biobank, who were free of NAFLD at baseline (2006-2010) were analyzed in this study. Of the above participants, 9816 participants have MRI-PDFF data, measured in 2014. Generalized linear models were used to evaluated association between the frequency of adding salt to foods with liver-PDFF; Cox proportional hazards models were used to estimate the association between the frequency of adding salt to foods and severe NAFLD risk. Results: During a median of 11 years of follow-up, 5,294 severe NAFLD cases were documented. Compared with participants who Never/Rarely added salt to foods, the adjusted Hazard Ratios (95% confidence interval) were 1.11 (1.04, 1.18), 1.27 (1.17, 1.37), and 1.45 (1.30, 1.62) across the groups of Sometimes, Usually, and Always, respectively (P-trend&amp;lt;0.001). The liver-PDFF values were 4.7 % (95% CI, 3.9, 5.5), 5.1% (4.3, 5.9), 5.2% (4.4, 6.0) and 5.5% (4.5-6.4) in the groups of Never/Rarely, Sometimes, Usually, and Always added salt to foods, respectively (P-trend&amp;lt;0.001). In sensitivity analyses, we replaced the frequency of adding salt to foods with estimated 24-hour urinary sodium extraction and found similar significant associations. Conclusions: Our findings indicate that high sodium intake is associated with higher risk of severe NAFLD. Disclosure H. Ma: None. X. Wang: None. X. Li: None. Y. Heianza: None. L. Qi: None.

Abstract #1400837: Skewness in Body Fat Distribution Pattern Links to Specific Cardiometabolic Disease Risk Profiles

Research on body fat distribution illustrates a heterogeneity within obesity and indicates that the pattern in which a person carries their fat could help determine each individual’s cardiometabolic risk profile. The aim of this study was to evaluate the association between balance of different fat compartments (visceral, subcutaneous, and liver) with incident type 2 diabetes (T2D) and cardiovascular disease (CVD) in the UK Biobank imaging study. Magnetic resonance images were collected in 40,174 participants using a 6-minute neck-to-knee protocol and analyzed for visceral adipose tissue (VAT) volume, abdominal subcutaneous adipose tissue (aSAT) volume, and liver proton density fat fraction (LF) using AMRA® Researcher. To assess body fat distribution patterns independent of BMI, personalized body fat z-scores (VATz, aSATz, and LFz) were calculated for each participant using the distribution of least N=150 matched controls with the same sex and similar BMI. Participants without prevalent T2D and CVD (N=35,138), were partitioned in 3 ways: based on the balance between (1) VATz & LFz using z-scores=0 as cut-points (thus creating 4 groups: VATz< 0 & LFz< 0 (reference [lower VAT and LF than predicted by BMI]); VATz< 0 & LFz >0; VATz >0 & LFz< 0; VATz >0 & LFz >0, (2) VATz & aSATz, and (3) LFz & aSATz. Logistic regression and Cox proportional-hazards models were used to investigate the association of the balance between body fat z-scores with incident T2D and CVD respectively. Models were crude and subsequently adjusted for sex, age, and BMI. The strongest association with incident T2D were found for VATz >0 & LFz >0 (crude odds ratio (cOR) 4.31, 95% CI 2.83-6.78, p< 0.001), VATz >0 & aSATz< 0 (cOR 4.43, 95% CI 2.85-7.11, p< 0.001), and LFz >0 & aSATz< 0 (cOR 2.47, 95% CI 1.62-3.83, p< 0.001). When adjusted for sex, age, and BMI, those with VATz >0 and/or LFz >0 remained significant. For incident CVD, the strongest associations were found for VATz >0 & LFz< 0 (crude hazard ratio (cHR) 1.53, 95% CI 1.34-1.76, p< 0.001) and VATz >0 & aSATz< 0 (cHR 1.54, 95% CI 1.34-1.76, p< 0.001). When adjusted for sex, age, and BMI, only VATz >0 & LFz< 0 remained significant. Excessive accumulation of VAT in relation to BMI (VATz >0) was consistently linked to both T2D and CVD. Excessive accumulation of LF in relation to BMI (LFz >0) was linked to T2D only. Groups with skewed fat distribution patterns showed the highest risk for incident CVD (VATz >0 & LFz< 0 and VATz >0 & aSATz< 0) and T2D (VATz >0 & aSATz< 0). Descriptions of body fat distribution pattern could inform diagnosis and treatment strategies for obesity and related conditions.

Liver PDFF estimation using a multi-decoder water-fat separation neural network with a reduced number of echoes

ObjectiveTo accurately estimate liver PDFF from chemical shift-encoded (CSE) MRI using a deep learning (DL)-based Multi-Decoder Water-Fat separation Network (MDWF-Net), that operates over complex-valued CSE-MR images with only 3 echoes.MethodsThe proposed MDWF-Net and a U-Net model were independently trained using the first 3 echoes of MRI data from 134 subjects, acquired with conventional 6-echoes abdomen protocol at 1.5 T. Resulting models were then evaluated using unseen CSE-MR images obtained from 14 subjects that were acquired with a 3-echoes CSE-MR pulse sequence with a shorter duration compared to the standard protocol. Resulting PDFF maps were qualitatively assessed by two radiologists, and quantitatively assessed at two corresponding liver ROIs, using Bland Altman and regression analysis for mean values, and ANOVA testing for standard deviation (STD) (significance level: .05). A 6-echo graph cut was considered ground truth.ResultsAssessment of radiologists demonstrated that, unlike U-Net, MDWF-Net had a similar quality to the ground truth, despite it considered half of the information. Regarding PDFF mean values at ROIs, MDWF-Net showed a better agreement with ground truth (regression slope = 0.94, R2 = 0.97) than U-Net (regression slope = 0.86, R2 = 0.93). Moreover, ANOVA post hoc analysis of STDs showed a statistical difference between graph cuts and U-Net (p < .05), unlike MDWF-Net (p = .53).ConclusionMDWF-Net showed a liver PDFF accuracy comparable to the reference graph cut method, using only 3 echoes and thus allowing a reduction in the acquisition times.Clinical relevance statementWe have prospectively validated that the use of a multi-decoder convolutional neural network to estimate liver proton density fat fraction allows a significant reduction in MR scan time by reducing the number of echoes required by 50%.Key Points• Novel water-fat separation neural network allows for liver PDFF estimation by using multi-echo MR images with a reduced number of echoes.• Prospective single-center validation demonstrated that echo reduction leads to a significant shortening of the scan time, compared to standard 6-echo acquisition.• Qualitative and quantitative performance of the proposed method showed no significant differences in PDFF estimation with respect to the reference technique.

Genetic variants in HFE are associated with non-alcoholic fatty liver disease in lean individuals

Background & AimsAround 20% of patients with non-alcoholic fatty liver disease (NAFLD) are lean. Increasing evidence suggests that lean NAFLD is a unique subtype of the disease. We aimed to explore the metabolic profile, genetic basis, causal risk factors, and clinical sequelae underlying lean NAFLD. MethodsNAFLD was diagnosed by whole liver proton density fat fraction ≥5%. Whole liver proton density fat fraction and hepatic iron were quantified using magnetic resonance imaging in the UK Biobank. Individuals in this study were stratified according to the World Health Organization criteria of obesity, into lean, overweight, and obese. Mediation analysis, Mendelian randomisation analysis, and Bayesian networks were used to identify a risk factor or a clinical sequela of lean/obese NAFLD. ResultsLean NAFLD manifested a distinct metabolic profile, featured by elevated hepatic iron and fasting glucose. Four loci, namely, HFE rs1800562, SLC17A3-SLC17A2-TRIM38 rs9348697, PNPLA3 rs738409, and TM6SF2 rs58542926, were associated with lean NAFLD (p <5 × 10-8). HFE rs1800562 was specifically associated with lean NAFLD and demonstrated a significant mediation effect through elevating hepatic iron. Type 2 diabetes was the most pronounced clinical sequela of lean NAFLD, followed by liver cirrhosis. ConclusionsOur study suggested that HFE plays a potential steatogenic role rather than regulating iron homoeostasis in patients with lean NAFLD. The increased liver iron deposition is associated with lean NAFLD, whereas obese NAFLD is not related to hepatic iron. The clinical management of patients with lean NAFLD shall be concerned with the prevention and treatment of type 2 diabetes and liver cirrhosis. Impact and implicationsLean NAFLD has a distinct natural history from obese NAFLD. This study underscored liver iron content and the genetic variant of the iron homoeostasis gene HFE as major risks of lean NAFLD, in addition to the unique metabolic profile. The development of type 2 diabetes or liver cirrhosis shall be closely monitored and prevented in patients with lean NAFLD.

Is adiposity associated with white matter microstructural health and intelligence differently in males and females?

The role of vascular risk factors in age-related brain degeneration has long been the subject of intense study, but the role of obesity remains understudied. Given known sex differences in fat storage and usage, this study investigates sex differences in the association between adiposity and white matter microstructural integrity, an important early marker of brain degeneration. This study assesses the associations between adiposity (abdominal fat ratio and liver proton density fat fraction) and brain health (measures of intelligence and whitematter microstructure using diffusion-tensor imaging [DTI]) in a group of UK Biobank participants. This study finds that intelligence and DTI metrics are indeed associated with adiposity differently in males and females. These sex differences are distinct from those in the associations of DTI metrics with age and blood pressure. Taken together, these findings suggest that there are inherent sex-driven differences in how brain health is associated with obesity.

Imaging Non-alcoholic Fatty Liver Disease Model Using H-1 and F-19 MRI.

We explore the use of intravenously delivered perfluorocarbon (PFC) nanoemulsion and 19F MRI for detecting inflammation in a mouse model of non-alcoholic fatty liver disease (NAFLD). Correlative studies of 1H-based liver proton density fat fraction (PDFF) and T1 measurements and histology are also evaluated. C57BL/6 mice were fed standard or high-fat diet (HFD) for 6weeks to induce NAFLD. 1H MRI measurements of PDFF and T1 relaxation time were performed at baseline to assess NAFLD onset prior to administration of a PFC nanoemulsion to enable 19F MRI of liver PFC uptake. 1H and 19F MRI biomarkers were acquired at 2, 21, and 42days post-PFC to assess changes. Histopathology of liver tissue was performed at experimental endpoint. Significant increases in liver volume, PDFF, and total PFC uptake were noted in HFD mice compared to Std diet mice. Liver fluorine density and T1 relaxation time were significantly reduced in HFD mice. We demonstrated longitudinal quantification of multiple MRI biomarkers of disease in NAFLD mice. The changes in liver PFC uptake in HFD mice were compared with healthy mice that suggests that 19F MRI may be a viable biomarker of liver pathology.

Adverse muscle composition is a significant risk factor for all-cause mortality in NAFLD

Adverse muscle composition (MC) (i.e., low muscle volume and high muscle fat) has previously been linked to poor functional performance and comorbidities in non-alcoholic fatty liver disease (NAFLD). In this study we aimed to investigate associations of all-cause mortality with liver fat, NAFLD, and MC in the UK Biobank imaging study. Magnetic resonance images of 40,174 participants were analyzed for liver proton density fat fraction (PDFF), thigh fat-free muscle volume (FFMV) z-score, and muscle fat infiltration (MFI) using the AMRA® Researcher. Participants with NAFLD were sex-, age-, and BMI-matched to participants without NAFLD with low alcohol consumption. Adverse MC was identified using previously published cut-offs. All-cause mortality was investigated using Cox regression. Models within NAFLD were crude and subsequently adjusted for sex, age, BMI (M1), hand grip strength, physical activity, smoking, alcohol (M2), and previous cancer, coronary heart disease, type 2 diabetes (M3). A total of 5,069 participants had NAFLD. During a mean (±SD) follow-up of 3.9 (±1.4) years, 150 out of the 10,138 participants (53% men, age 64.4 [±7.6] years, BMI 29.7 [±4.4] kg/m2) died. In the matched dataset, neither NAFLD nor liver PDFF were associated with all-cause mortality, while all MC variables achieved significance. Within NAFLD, adverse MC, MFI and FFMV z-score were significantly associated with all-cause mortality and remained so in M1 and M2 (crude hazard ratios [HRs] 2.84, 95% CI 1.70-4.75, p <0.001; 1.15, 95% CI 1.07-1.24, p <0.001; 0.70, 95% CI 0.55-0.88, p <0.001). In M3, the relationship was attenuated for adverse MC and FFMV z-score (adjusted HRs 1.72, 95% CI 1.00-2.98, p=0.051; 0.77, 95% CI 0.58-1.02, p=0.069) but remained significant for MFI (adjusted HR 1.13, 95% CI 1.01-1.26, p=0.026). Neither NAFLD nor liver PDFF was predictive of all-cause mortality. Adverse MC was a strong predictor of all-cause mortality in individuals with NAFLD. Individuals with fatty liver disease and poor muscle health more often suffer from poor functional performance and comorbidities. This study shows that they are also at a higher risk of dying. The study results indicate that measuring muscle health (the patient's muscle volume and how much fat they have in their muscles) could help in the early detection of high-risk patients and enable targeted preventative care.

Uncertainty-aware physics-driven deep learning network for free-breathing liver fat and R2 * quantification using self-gated stack-of-radial MRI.

To develop a deep learning-based method for rapid liver proton-density fat fraction (PDFF) and R2 * quantification with built-in uncertainty estimation using self-gated free-breathing stack-of-radial MRI. This work developed an uncertainty-aware physics-driven deep learning network (UP-Net) to (1) suppress radial streaking artifacts because of undersampling after self-gating, (2) calculate accurate quantitative maps, and (3) provide pixel-wise uncertainty maps. UP-Net incorporated a phase augmentation strategy, generative adversarial network architecture, and an MRI physics loss term based on a fat-water and R2 * signal model. UP-Net was trained and tested using free-breathing multi-echo stack-of-radial MRI data from 105 subjects. UP-Net uncertainty scores were calibrated in a validation dataset and used to predict quantification errors for liver PDFF and R2 * in a testing dataset. Compared with images reconstructed using compressed sensing (CS), UP-Net achieved structural similarity index >0.87 and normalized root mean squared error <0.18. Compared with reference quantitative maps generated using CS and graph-cut (GC) algorithms, UP-Net achieved low mean differences (MD) for liver PDFF (-0.36%) and R2 * (-0.37 s-1 ). Compared with breath-holding Cartesian MRI results, UP-Net achieved low MD for liver PDFF (0.53%) and R2 * (6.75 s-1 ). UP-Net uncertainty scores predicted absolute liver PDFF and R2 * errors with low MD of 0.27% and 0.12 s-1 compared to CS + GC results. The computational time for UP-Net was 79 ms/slice, whereas CS + GC required 3.2 min/slice. UP-Net rapidly calculates accurate liver PDFF and R2 * maps from self-gated free-breathing stack-of-radial MRI. The pixel-wise uncertainty maps from UP-Net predict quantification errors in the liver.

Atherogenic index of plasma combined with waist circumference and body mass index to predict metabolic-associated fatty liver disease.

Early identification of metabolic-associated fatty liver disease (MAFLD) is urgent. Atherogenic index of plasma (AIP) is a reference predictor of obesity-related diseases, but its predictive value for MAFLD remains unclear. No studies have reported whether its combination with waist circumference (WC) and body mass index (BMI) can improve the predictive performance for MAFLD. To systematically explore the relationship between AIP and MAFLD and evaluate its predictive value for MAFLD and to pioneer a novel noninvasive predictive model combining AIP, WC, and BMI while validating its predictive performance for MAFLD. This cross-sectional study consecutively enrolled 864 participants. Multivariate logistic regression analysis and receiver operating characteristic curve were used to evaluate the relationship between AIP and MAFLD and its predictive power for MAFLD. The novel prediction model A-W-B combining AIP, WC, and BMI to predict MAFLD was established, and internal verification was completed by magnetic resonance imaging diagnosis. Subjects with higher AIP exhibited a significantly increased risk of MAFLD, with an odds ratio of 12.420 (6.008-25.675) for AIP after adjusting for various confounding factors. The area under receiver operating characteristic curve of the A-W-B model was 0.833 (0.807-0.858), which was significantly higher than that of AIP, WC, and BMI (all P < 0.05). Subgroup analysis illustrated that the A-W-B model had significantly higher area under receiver operating characteristic curves in female, young and nonobese subgroups (all P < 0.05). The best cutoff values for the A-W-B model to predict MAFLD in males and females were 0.5932 and 0.4105, respectively. Additionally, in the validation set, the area under receiver operating characteristic curve of the A-W-B model to predict MAFLD was 0.862 (0.791-0.916). The A-W-B level was strongly and positively associated with the liver proton density fat fraction (r = 0.630, P < 0.001) and significantly increased with the severity of MAFLD (P < 0.05). AIP was strongly and positively associated with the risk of MAFLD and can be a reference predictor for MAFLD. The novel prediction model A-W-B combining AIP, WC, and BMI can significantly improve the predictive ability of MAFLD and provide better services for clinical prediction and screening of MAFLD.

Prospective characterization of incident hepatic steatosis in pediatric and adolescent patients after total pancreatectomy with islet autotransplantation

BackgroundHepatic steatosis has been described as a common finding in adults following total pancreatectomy with islet autotransplantation (TPIAT) but it is unknown if this occurs in children and adolescents. ObjectivesTo define the frequency of post-TPIAT hepatic steatosis in a sample of children and adolescents and to identify clinical predictors of incident steatosis post-TPIAT. MethodsIn this prospective study, consecutive participants at least 1-month post-TPIAT underwent a liver MRI with proton density fat fraction (PDFF) and blood draw at our pediatric academic medical center between April 2021 and January 2022. Comparison clinical pre-TPIAT liver MRI or ultrasound and insulin use and graft function data were extracted from the medical record. T-tests were used for the comparison of means across continuous variables between participants with and without post-TPIAT steatosis. ResultsA total of 20 participants (mean: 13 ± 4 years; 12 female) were evaluated. Mean liver PDFF at research MRI was 7.4 ± 6.2% (range: 2–25%). Seven participants (35%) had categorical hepatic steatosis (PDFF>5%) post-TPIAT, five of whom had pre-TPIAT steatosis, reflecting a 13% (2/15; 95% CI: 2–40%) incidence of post-TPIAT steatosis. Participant characteristics were not significantly different between subgroups with and without post-TPIAT steatosis. Mean PDFF at research MRI was not different between graft function subgroups (7.5% optimal/good vs. 7.3% marginal/failure; p = .96). ConclusionOur study shows a moderate prevalence but low incidence of hepatic steatosis in a small sample of children and adolescents post-TPIAT. This study raises questions about a causal relationship between TPIAT and hepatic steatosis.