Machine learning algorithm improves the detection of NASH (NAS-based) and at-risk NASH: A development and validation study.

BACKGROUND AND AIMS: Detecting NASH remains challenging, while at-risk NASH (steatohepatitis and F≥ 2) tends to progress and is of interest for drug development and clinical application. We developed prediction models by supervised machine learning techniques, with clinical data and biomarkers to stage and grade patients with NAFLD. APPROACH AND RESULTS: Learning data were collected in the Liver Investigation: Testing Marker Utility in Steatohepatitis metacohort (966 biopsy-proven NAFLD adults), staged and graded according to NASH CRN. Conditions of interest were the clinical trial definition of NASH (NAS ≥ 4;53%), at-risk NASH (NASH with F ≥ 2;35%), significant (F ≥ 2;47%), and advanced fibrosis (F ≥ 3;28%). Thirty-five predictors were included. Missing data were handled by multiple imputations. Data were randomly split into training/validation (75/25) sets. A gradient boosting machine was applied to develop 2 models for each condition: clinical versus extended (clinical and biomarkers). Two variants of the NASH and at-risk NASH models were constructed: direct and composite models.Clinical gradient boosting machine models for steatosis/inflammation/ballooning had AUCs of 0.94/0.79/0.72. There were no improvements when biomarkers were included. The direct NASH model produced AUCs (clinical/extended) of 0.61/0.65. The composite NASH model performed significantly better (0.71) for both variants. The composite at-risk NASH model had an AUC of 0.83 (clinical and extended), an improvement over the direct model. Significant fibrosis models had AUCs (clinical/extended) of 0.76/0.78. The extended advanced fibrosis model (0.86) performed significantly better than the clinical version (0.82). CONCLUSIONS: Detection of NASH and at-risk NASH can be improved by constructing independent machine learning models for each component, using only clinical predictors. Adding biomarkers only improved the accuracy of fibrosis.

Noninvasive assessment of liver disease severity in patients with nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes.

BACKGROUND AND AIMS: We evaluated the diagnostic accuracy of simple, noninvasive tests (NITs) in NAFLD patients with type 2 diabetes (T2D). METHODS AND RESULTS: This was an individual patient data meta-analysis of 1780 patients with biopsy-proven NAFLD and T2D. The index tests of interest were FIB-4, NAFLD Fibrosis Score (NFS), aspartate aminotransferase-to-platelet ratio index, liver stiffness measurement (LSM) by vibration-controlled transient elastography, and AGILE 3+. The target conditions were advanced fibrosis, NASH, and fibrotic NASH(NASH plus F2-F4 fibrosis). The diagnostic performance of noninvasive tests. individually or in sequential combination, was assessed by area under the receiver operating characteristic curve and by decision curve analysis. Comparison with 2278 NAFLD patients without T2D was also made. In NAFLD with T2D LSM and AGILE 3+ outperformed, both NFS and FIB-4 for advanced fibrosis (area under the receiver operating characteristic curve:LSM 0.82, AGILE 3+ 0.82, NFS 0.72, FIB-4 0.75, aspartate aminotransferase-to-platelet ratio index 0.68; p < 0.001 of LSM-based versus simple serum tests), with an uncertainty area of 12%-20%. The combination of serum-based with LSM-based tests for advanced fibrosis led to a reduction of 40%-60% in necessary LSM tests. Decision curve analysis showed that all scores had a modest net benefit for ruling out advanced fibrosis at the risk threshold of 5%-10% of missing advanced fibrosis. LSM and AGILE 3+ outperformed both NFS and FIB-4 for fibrotic NASH (area under the receiver operating characteristic curve:LSM 0.79, AGILE 3+ 0.77, NFS 0.71, FIB-4 0.71; p < 0.001 of LSM-based versus simple serum tests). All noninvasive scores were suboptimal for diagnosing NASH. CONCLUSIONS: LSM and AGILE 3+ individually or in low availability settings in sequential combination after FIB-4 or NFS have a similar good diagnostic accuracy for advanced fibrosis and an acceptable diagnostic accuracy for fibrotic NASH in NAFLD patients with T2D.

Liver fibrosis phenotyping and severity scoring by quantitative image analysis of biopsy slides.

BACKGROUND & AIMS: Digital pathology image analysis can phenotype liver fibrosis using histological traits that reflect collagen content, morphometry and architecture. Here, we aimed to calculate fibrosis severity scores to quantify these traits. METHODS: Liver biopsy slides were categorised by Ishak stage and aetiology. We used a digital pathology technique to calculate four fibrosis severity scores: Architecture Composite Score (ACS), Collagen Composite Score (CCS), Morphometric Composite Score (MCS) and Phenotypic Fibrosis Composite Score (PH-FCS). We compared how these scores varied according to disease stage and aetiology. RESULTS: We included 80 patients (40% female, mean age 59.0 years, mean collagen proportionate area 17.1%) with mild (F0-2, n = 28), moderate (F3-4, n = 17) or severe (F5-6, n = 35) fibrosis. All four aetiology independent scores corelated with collagen proportionate area (ACS: rp = .512, CCS: rp = .727, MCS: rp = .777, PFCS: r = .772, p < .01 for all) with significant differences between moderate and severe fibrosis (p < .05). ACS increased primarily between moderate and severe fibrosis (by 95% to 226% depending on underlying aetiology), whereas MCS and CCS accumulation was more varied. We used 28 qFTs that distinguished between autoimmune- and alcohol-related liver disease to generate an MCS that significantly differed between mild and severe fibrosis for these aetiologies (p < .05). CONCLUSIONS: We describe four aetiology-dependent and -independent severity scores that quantify fibrosis architecture, collagen content and fibre morphometry. This approach provides additional insight into how progression of architectural changes and accumulation of collagen may differ depending on underlying disease aetiology.

Diagnostic accuracy of non-invasive tests to screen for at-risk MASH-An individual participant data meta-analysis.

BACKGROUND & AIMS: There is a need to reduce the screen failure rate (SFR) in metabolic dysfunction-associated steatohepatitis (MASH) clinical trials (MASH+F2-3; MASH+F4) and identify people with high-risk MASH (MASH+F2-4) in clinical practice. We aimed to evaluate non-invasive tests (NITs) screening approaches for these target conditions. METHODS: This was an individual participant data meta-analysis for the performance of NITs against liver biopsy for MASH+F2-4, MASH+F2-3 and MASH+F4. Index tests were the FibroScan-AST (FAST) score, liver stiffness measured using vibration-controlled transient elastography (LSM-VCTE), the fibrosis-4 score (FIB-4) and the NAFLD fibrosis score (NFS). Area under the receiver operating characteristics curve (AUROC) and thresholds including those that achieved 34% SFR were reported. RESULTS: We included 2281 unique cases. The prevalence of MASH+F2-4, MASH+F2-3 and MASH+F4 was 31%, 24% and 7%, respectively. Area under the receiver operating characteristics curves for MASH+F2-4 were .78, .75, .68 and .57 for FAST, LSM-VCTE, FIB-4 and NFS. Area under the receiver operating characteristics curves for MASH+F2-3 were .73, .67, .60, .58 for FAST, LSM-VCTE, FIB-4 and NFS. Area under the receiver operating characteristics curves for MASH+F4 were .79, .84, .81, .76 for FAST, LSM-VCTE, FIB-4 and NFS. The sequential combination of FIB-4 and LSM-VCTE for the detection of MASH+F2-3 with threshold of .7 and 3.48, and 5.9 and 20 kPa achieved SFR of 67% and sensitivity of 60%, detecting 15 true positive cases from a theoretical group of 100 participants at the prevalence of 24%. CONCLUSIONS: Sequential combinations of NITs do not compromise diagnostic performance and may reduce resource utilisation through the need of fewer LSM-VCTE examinations.

An individual patient data meta-analysis to determine cut-offs for and confounders of NAFLD-fibrosis staging with magnetic resonance elastography.

BACKGROUND & AIMS: We conducted an individual patient data meta-analysis to establish stiffness cut-off values for magnetic resonance elastography (MRE) in staging liver fibrosis and to assess potential confounding factors. METHODS: A systematic review of the literature identified studies reporting MRE data in patients with NAFLD. Data were obtained from the corresponding authors. The pooled diagnostic cut-off value for the various fibrosis stages was determined in a two-stage meta-analysis. Multilevel modelling methods were used to analyse potential confounding factors influencing the diagnostic accuracy of MRE in staging liver fibrosis. RESULTS: Eight independent cohorts comprising 798 patients were included in the meta-analysis. The area under the receiver operating characteristic curve (AUROC) for MRE in detecting significant fibrosis was 0.92 (sensitivity, 79%; specificity, 89%). For advanced fibrosis, the AUROC was 0.92 (sensitivity, 87%; specificity, 88%). For cirrhosis, the AUROC was 0.94 (sensitivity, 88%, specificity, 89%). Cut-offs were defined to explore concordance between MRE and histopathology: ≥F2, 3.14 kPa (pretest probability, 39.4%); ≥F3, 3.53 kPa (pretest probability, 24.1%); and F4, 4.45 kPa (pretest probability, 8.7%). In generalized linear mixed model analysis, histological steatohepatitis with higher inflammatory activity (odds ratio 2.448, 95% CI 1.180-5.079, p <0.05) and high gamma-glutamyl transferase (GGT) concentration (>120U/L) (odds ratio 3.388, 95% CI 1.577-7.278, p <0.01] were significantly associated with elevated liver stiffness, and thus affecting accuracy in staging early fibrosis (F0-F1). Steatosis, as measured by magnetic resonance imaging proton density fat fraction, and body mass index(BMI) were not confounders. CONCLUSIONS: MRE has excellent diagnostic performance for significant, advanced fibrosis and cirrhosis in patients with NAFLD. Elevated inflammatory activity and GGT level may lead to overestimation of early liver fibrosis, but anthropometric measures such as BMI or the degree of steatosis do not. IMPACT AND IMPLICATIONS: This individual patient data meta-analysis of eight international cohorts, including 798 patients, demonstrated that MRE achieves excellent diagnostic accuracy for significant, advanced fibrosis and cirrhosis in patients with NAFLD. Cut-off values (significant fibrosis, 3.14 kPa; advanced fibrosis, 3.53 kPa; and cirrhosis, 4.45 kPa) were established. Elevated inflammatory activity and gamma-glutamyltransferase level may affect the diagnostic accuracy of MRE, leading to overestimation of liver fibrosis in early stages. We observed no impact of diabetes, obesity, or any other metabolic disorder on the diagnostic accuracy of MRE.

Detection and alterations of acetylcarnitine (AC) in human liver by 1 H MRS at 3T after supplementation with l-carnitine.

PURPOSE: Acetylcarnitine can be assessed in vivo using proton MRS (1 H-MRS) with long TEs and this has been previously applied successfully in muscle. The aim of this study was to evaluate a 1 H-MRS technique for liver acetylcarnitine quantification in healthy humans before and after l-carnitine supplementation. METHOD: Baseline acetylcarnitine levels were quantified using a STEAM sequence with prolonged TE in 15 healthy adults. Using STEAM with four different TEs was evaluated in phantoms. To assess reproducibility of the measurements, five of the participants had repeated 1 H-MRS without receiving l-carnitine supplementation. To determine if liver acetylcarnitine could be changed after l-carnitine supplementation, acetylcarnitine was quantified 2 h after intravenous l-carnitine supplementation (50 mg/kg body weight) in the other 10 participants. Hepatic lipids were also quantified from the 1 H-MRS spectra. RESULTS: There was good separation between the acetylcarnitine and fat in the phantoms using TE = 100 ms. Hepatic acetylcarnitine levels were reproducible (coefficient of reproducibility = 0.049%) and there was a significant (p < 0.001) increase in the relative abundance after a single supplementation of l-carnitine. Hepatic allylic, methyl, and methylene peaks were not altered by l-carnitine supplementation in healthy volunteers. CONCLUSION: Our results demonstrate that our 1 H-MRS technique could be used to measure acetylcarnitine in the liver and detect changes following intravenous supplementation in healthy adults despite the presence of lipids. Our techniques should be explored further in the study of fatty liver disease, where acetylcarnitine is suggested to be altered due to hepatic inflexibilities.

Clinical Utility of Magnetic Resonance Imaging Biomarkers for Identifying Nonalcoholic Steatohepatitis Patients at High Risk of Progression: A Multicenter Pooled Data and Meta-Analysis.

BACKGROUND & AIMS: Nonalcoholic fatty liver disease (NAFLD) is increasing in prevalence worldwide. NAFLD is associated with excess risk of all-cause mortality, and its progression to nonalcoholic steatohepatitis (NASH) and fibrosis accounts for a growing proportion of cirrhosis and hepatocellular cancer and thus is a leading cause of liver transplant worldwide. Noninvasive precise methods to identify patients with NASH and NASH with significant disease activity and fibrosis are crucial when the disease is still modifiable. The aim of this study was to examine the clinical utility of corrected T1 (cT1) vs magnetic resonance imaging (MRI) liver fat for identification of NASH participants with nonalcoholic fatty liver disease activity score ≥4 and fibrosis stage (F) ≥2 (high-risk NASH). METHODS: Data from five clinical studies (n = 543) with participants suspected of NAFLD were pooled or used for individual participant data meta-analysis. The diagnostic accuracy of the MRI biomarkers to stratify NASH patients was determined using the area under the receiver operating characteristic curve (AUROC). RESULTS: A stepwise increase in cT1 and MRI liver fat with increased NAFLD severity was shown, and cT1 was significantly higher in participants with high-risk NASH. The diagnostic accuracy (AUROC) of cT1 to identify patients with NASH was 0.78 (95% CI, 0.74-0.82), for liver fat was 0.78 (95% CI, 0.73-0.82), and when combined with MRI liver fat was 0.82 (95% CI, 0.78-0.85). The diagnostic accuracy of cT1 to identify patients with high-risk NASH was good (AUROC = 0.78; 95% CI, 0.74-0.82), was superior to MRI liver fat (AUROC = 0.69; 95% CI, 0.64-0.74), and was not substantially improved by combining it with MRI liver fat (AUROC = 0.79; 95% CI, 0.75-0.83). The meta-analysis showed similar performance to the pooled analysis for these biomarkers. CONCLUSIONS: This study shows that quantitative MRI-derived biomarkers cT1 and liver fat are suitable for identifying patients with NASH, and cT1 is a better noninvasive technology than liver fat to identify NASH patients at greatest risk of disease progression. Therefore, MRI cT1 and liver fat have important clinical utility to help guide the appropriate use of interventions in NAFLD and NASH clinical care pathways.

A novel serum metabolomic panel distinguishes IgG4-related sclerosing cholangitis from primary sclerosing cholangitis.

BACKGROUND & AIMS: Primary sclerosing cholangitis (PSC) and IgG4-related sclerosing cholangitis (IgG4-SC) are chronic fibro-inflammatory immune-mediated hepatobiliary conditions that are challenging to distinguish in a clinical setting. Accurate non-invasive biomarkers for discriminating PSC and IgG4-SC are important to ensure a correct diagnosis, prompt therapy and adequate cancer surveillance. METHODS: We performed nuclear magnetic resonance (NMR)-based metabolomic profiling using serum samples collected prospectively from patients with PSC (n = 100), IgG4-SC (n = 23) and healthy controls (HC; n = 16). RESULTS: Multivariate analysis of the serum metabolome discriminated PSC from IgG4-SC with greater accuracy (AUC 0.95 [95%CI 0.90-0.98]) than IgG4 titre (AUC 0.87 [95%CI 0.79-0.94]). When inflammatory bowel disease (IBD) was excluded as a comorbid condition (IgG4-SC n = 20, PSC n = 22), the diagnostic AUC increased to 1.0, suggesting that the metabolome differences identified are not a result of the increased prevalence of IBD in PSC relative to IgG4-SC patients. Serum lactate (p < .0001), glucose (p < .01) and glutamine (p < .01) metabolites were increased in IgG4-related disease (IgG4-RD) and IgG4-SC individuals compared to PSC, whereas mobile choline (p < .05), 3-hydroxybutyric acid (p < .01) and -CH3 lipoprotein resonances (p < .01) were decreased. CONCLUSIONS: Taken together, serum metabolomic profiling has the potential to be incorporated as a diagnostic criterion, independent of IgG4 titre, to improve the diagnosis of IgG4-RD and help distinguish IgG4-SC from PSC.

Diagnostic accuracy of elastography and magnetic resonance imaging in patients with NAFLD: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Vibration-controlled transient elastography (VCTE), point shear wave elastography (pSWE), 2-dimensional shear wave elastography (2DSWE), magnetic resonance elastography (MRE), and magnetic resonance imaging (MRI) have been proposed as non-invasive tests for patients with non-alcoholic fatty liver disease (NAFLD). This study evaluated their diagnostic accuracy for liver fibrosis and non-alcoholic steatohepatitis (NASH). METHODS: PubMED/MEDLINE, EMBASE and the Cochrane Library were searched for studies examining the diagnostic accuracy of these index tests, against histology as the reference standard, in adult patients with NAFLD. Two authors independently screened and assessed methodological quality of studies and extracted data. Summary estimates of sensitivity, specificity and area under the curve (sAUC) were calculated for fibrosis stages and NASH, using a random effects bivariate logit-normal model. RESULTS: We included 82 studies (14,609 patients). Meta-analysis for diagnosing fibrosis stages was possible in 53 VCTE, 11 MRE, 12 pSWE and 4 2DSWE studies, and for diagnosing NASH in 4 MRE studies. sAUC for diagnosis of significant fibrosis were: 0.83 for VCTE, 0.91 for MRE, 0.86 for pSWE and 0.75 for 2DSWE. sAUC for diagnosis of advanced fibrosis were: 0.85 for VCTE, 0.92 for MRE, 0.89 for pSWE and 0.72 for 2DSWE. sAUC for diagnosis of cirrhosis were: 0.89 for VCTE, 0.90 for MRE, 0.90 for pSWE and 0.88 for 2DSWE. MRE had sAUC of 0.83 for diagnosis of NASH. Three (4%) studies reported intention-to-diagnose analyses and 15 (18%) studies reported diagnostic accuracy against pre-specified cut-offs. CONCLUSIONS: When elastography index tests are acquired successfully, they have acceptable diagnostic accuracy for advanced fibrosis and cirrhosis. The potential clinical impact of these index tests cannot be assessed fully as intention-to-diagnose analyses and validation of pre-specified thresholds are lacking. LAY SUMMARY: Non-invasive tests that measure liver stiffness or use magnetic resonance imaging (MRI) have been suggested as alternatives to liver biopsy for assessing the severity of liver scarring (fibrosis) and fatty inflammation (steatohepatitis) in patients with non-alcoholic fatty liver disease (NAFLD). In this study, we summarise the results of previously published studies on how accurately these non-invasive tests can diagnose liver fibrosis and inflammation, using liver biopsy as the reference. We found that some techniques that measure liver stiffness had a good performance for the diagnosis of severe liver scarring.

Hydration and glycogen affect T1 relaxation times of liver tissue.

T1 mapping is a useful tool for the assessment of patients with nonalcoholic fatty liver disease but still suffers from a large unexplained variance in healthy subjects. This study aims to characterize the potential effects of liver glycogen concentration and body hydration status on liver shortened modified Look-Locker inversion recovery (shMOLLI) T1 measurements. Eleven glycogen phantoms and 12 healthy volunteers (mean age: 31 years, three females) were scanned at 3 T using inversion recovery spin echo, multiple contrast spin echo (in phantoms), shMOLLI T1 mapping, multiple-echo spoiled gradient recalled echo and 13 C spectroscopy (in healthy volunteers). Phantom r1 and r2 relaxivities were determined from measured T1 and T2 values. Participants underwent a series of five metabolic experiments to vary their glycogen concentration and hydration levels: feeding, food fasting, exercising, underhydration, and rehydration. Descriptive statistics were calculated for shMOLLI T1 , inferior vena cava to aorta cross-sectional area ratio (IVC/Ao) as a marker of body hydration status, glycogen concentration, T2 * and proton density fat fraction values. A linear mixed model for shMOLLI R1 was constructed to determine the effects of glycogen concentration and IVC/Ao ratio. The mean shMOLLI T1 after fasting was 737 ± 67 ms. The mean within-subject change was 80 ± 45 ms. The linear mixed model revealed a glycogen r1 relaxivity in volunteers (0.18 M-1 s-1 , p = 0.03) close to that determined in phantoms (0.28 M-1 s-1 ). A unit change in IVC/Ao ratio was associated with a drop of -0.113 s-1 in R1 (p < 0.001). This study demonstrated a dependence of liver shMOLLI T1 values on liver glycogen concentration and overall body hydration status. Interparticipant variation of hydration status should be minimized in future liver MRI studies. Additionally, caution is advised when interpreting liver T1 measurements in participants with excess liver glycogen.

Simple non-invasive scoring systems and histological scores in predicting mortality in patients with non-alcoholic fatty liver disease: A systematic review and meta-analysis.

BACKGROUND AND AIM: There is debate among the hepatology community regarding the simple non-invasive scoring systems and histological scores (even it was developed for histological classification) in predicting clinical outcomes in patients with non-alcoholic fatty liver disease (NAFLD). This study aimed to determine whether the presence of simple non-invasive scoring systems and histological scores could predict all-cause mortality, liver-related mortality, and liver disease decompensation (liver failure, cirrhosis, hepatocellular carcinoma, or decompensated liver disease). METHODS: The pooled hazard ratio of prognostic factors and incidence rate per 1000 person-years in patients with NAFLD was calculated and further adjusted by two different models of handling the duplicated data. RESULTS: A total of 19 longitudinal studies were included. Most simple non-invasive scoring systems (Fibrosis-4 Score, BARD, and aspartate aminotransferase-to-platelet ratio index ) and histological scores (NAFLD activity score, Brunt, and "steatosis, activity, and fibrosis" ) failed in predicting mortality, and only the NAFLD fibrosis score > 0.676 showed prognostic ability to all-cause mortality (four studies, 7564 patients, 118 352 person-years followed up, pooled hazard ratio 1.44, 95% confidence interval [CI] 1.05-1.96). The incidence rate per 1000 person-years of all-cause mortality, liver-related mortality, cardiovascular-related mortality, and liver disease decompensation resulted in a pooled incidence rate per 1000 person-years of 22.65 (14 studies, 95% CI 9.62-53.31), 3.19 (7 studies, 95% CI 1.14-8.93), 6.02 (6 studies, 95% CI 4.69-7.74), and 11.46 (4 studies, 95% CI 5.33-24.63), respectively. CONCLUSION: Non-alcoholic fatty liver disease fibrosis score showed promising prognostic value to all-cause mortality. Most present simple non-invasive scoring systems and histological scores failed to predict clinical outcomes.

Prognostic value of multiparametric magnetic resonance imaging, transient elastography and blood-based fibrosis markers in patients with chronic liver disease.

BACKGROUND & AIMS: Liver cT1 , liver T1 , transient elastography (TE) and blood-based biomarkers have independently been shown to predict clinical outcomes but have not been directly compared in a single cohort of patients. Our aim was to compare these tests' prognostic value in a cohort of patients with compensated chronic liver disease. METHODS: Patients with unselected compensated liver disease aetiologies had baseline assessments and were followed up for development of clinical outcomes, blinded to the imaging results. The prognostic value of non-invasive liver tests at prespecified thresholds was assessed for a combined clinical endpoint comprising ascites, variceal bleeding, hepatic encephalopathy, hepatocellular carcinoma, liver transplantation and mortality. RESULTS: One hundred and ninety-seven patients (61% male) with median age of 54 years were followed up for 693 patient-years (median (IQR) 43 (26-58) months). The main diagnoses were NAFLD (41%), viral hepatitis (VH, 25%) and alcohol-related liver disease (ArLD; 14%). During follow-up 14 new clinical events, and 11 deaths occurred. Clinical outcomes were predicted by liver cT1  > 825ms with HR 9.9 (95% CI: 1.29-76.4, P = .007), TE > 8kPa with HR 7.8 (95% CI: 0.97-62.3, P = .02) and FIB-4 > 1.45 with HR 4.09 (95% CI: 0.90-18.4, P = .05). In analysis taking into account technical failure and unreliability, liver cT1  > 825 ms could predict clinical outcomes (P = .03), but TE > 8kPa could not (P = .4). CONCLUSIONS: We provide further evidence that liver cT1 , TE and serum-based biomarkers can predict clinical outcomes, but when taking into account technical failure/unreliability, TE cut-offs perform worse than those of cT1 and blood biomarkers.

Mapping tissue water T1 in the liver using the MOLLI T1 method in the presence of fat, iron and B0 inhomogeneity.

Modified Look-Locker inversion recovery (MOLLI) T1 mapping sequences can be useful in cardiac and liver tissue characterization, but determining underlying water T1 is confounded by iron, fat and frequency offsets. This article proposes an algorithm that provides an independent water MOLLI T1 (referred to as on-resonance water T1 ) that would have been measured if a subject had no fat and normal iron, and imaging had been done on resonance. Fifteen NiCl2 -doped agar phantoms with different peanut oil concentrations and 30 adults with various liver diseases, nineteen (63.3%) with liver steatosis, were scanned at 3 T using the shortened MOLLI (shMOLLI) T1 mapping, multiple-echo spoiled gradient-recalled echo and 1 H MR spectroscopy sequences. An algorithm based on Bloch equations was built in MATLAB, and water shMOLLI T1 values of both phantoms and human participants were determined. The quality of the algorithm's result was assessed by Pearson's correlation coefficient between shMOLLI T1 values and spectroscopically determined T1 values of the water, and by linear regression analysis. Correlation between shMOLLI and spectroscopy-based T1 values increased, from r = 0.910 (P < 0.001) to r = 0.998 (P < 0.001) in phantoms and from r = 0.493 (for iron-only correction; P = 0.005) to r = 0.771 (for iron, fat and off-resonance correction; P < 0.001) in patients. Linear regression analysis revealed that the determined water shMOLLI T1 values in patients were independent of fat and iron. It can be concluded that determination of on-resonance water (sh)MOLLI T1 independent of fat, iron and macroscopic field inhomogeneities was possible in phantoms and human subjects.

Hepatic iron is the major determinant of serum ferritin in NAFLD patients.

BACKGROUND AND AIMS: Elevated serum ferritin is common in NAFLD, and is associated with more advanced disease and increased mortality. Hyperferritinaemia in NAFLD is often attributed to inflammation, while in other conditions ferritin closely reflects body iron stores. The aim of this study was to clarify the underlying cause of hyperferritinaemia in NAFLD. METHODS: Ferritin levels were examined with markers of iron status, inflammation and liver injury across the clinical spectrum of NAFLD using blood, tissue and magnetic resonance (MR) imaging. A separate larger group of NAFLD patients with hepatic iron staining and quantification were used for validation. RESULTS: Serum ferritin correlated closely with the iron regulatory hormone hepcidin, and liver iron levels determined by MR. Furthermore, ferritin levels reflected lower serum adiponectin, a marker of insulin resistance, and liver fat, but not cytokine or CRP levels. Ferritin levels differed according to fibrosis stage, increasing from early to moderate disease, and declining in cirrhosis. A similar pattern was found in the validation cohort of NAFLD patients, where ferritin levels were highest in those with macrophage iron deposition. Multivariate analysis revealed liver iron and hepcidin levels as the major determinants of serum ferritin. CONCLUSIONS: While hyperferritinaemia is associated with markers of liver injury and insulin resistance, serum hepcidin and hepatic iron are the strongest predictors of ferritin levels. These findings highlight the role of disordered iron homeostasis in the pathogenesis of NAFLD, suggesting that therapies aimed at correcting iron metabolism may be beneficial.

Phosphodiester content measured in human liver by in vivo 31 P MR spectroscopy at 7 tesla.

PURPOSE: Phosphorus (31 P) metabolites are emerging liver disease biomarkers. Of particular interest are phosphomonoester and phosphodiester (PDE) "peaks" that comprise multiple overlapping resonances in 31 P spectra. This study investigates the effect of improved spectral resolution at 7 Tesla (T) on quantifying hepatic metabolites in cirrhosis. METHODS: Five volunteers were scanned to determine metabolite T1 s. Ten volunteers and 11 patients with liver cirrhosis were scanned at 7T. Liver spectra were acquired in 28 min using a 16-channel 31 P array and 3D chemical shift imaging. Concentrations were calculated using γ-adenosine-triphosphate (γ-ATP) = 2.65 mmol/L wet tissue. RESULTS: T1 means ± standard deviations: phosphatidylcholine 1.05 ± 0.28 s, nicotinamide-adenine-dinucleotide (NAD+ ) 2.0 ± 1.0 s, uridine-diphosphoglucose (UDPG) 3.3 ± 1.4 s. Concentrations in healthy volunteers: α-ATP 2.74 ± 0.11 mmol/L wet tissue, inorganic phosphate 2.23 ± 0.20 mmol/L wet tissue, glycerophosphocholine 2.34 ± 0.46 mmol/L wet tissue, glycerophosphoethanolamine 1.50 ± 0.28 mmol/L wet tissue, phosphocholine 1.06 ± 0.16 mmol/L wet tissue, phosphoethanolamine 0.77 ± 0.14 mmol/L wet tissue, NAD+ 2.37 ± 0.14 mmol/L wet tissue, UDPG 2.00 ± 0.22 mmol/L wet tissue, phosphatidylcholine 1.38 ±â€Š0.31 mmol/L wet tissue. Inorganic phosphate and phosphatidylcholine concentrations were significantly lower in patients; glycerophosphoethanolamine concentrations were significantly higher (P < 0.05). CONCLUSION: We report human in vivo hepatic T1 s for phosphatidylcholine, NAD+ , and UDPG for the first time at 7T. Our protocol allows high signal-to-noise, repeatable measurement of metabolite concentrations in human liver. The splitting of PDE into its constituent peaks at 7T may allow more insight into changes in metabolism. Magn Reson Med 78:2095-2105, 2017. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

A model for hepatic fibrosis: the competing effects of cell loss and iron on shortened modified Look-Locker inversion recovery T1 (shMOLLI-T1 ) in the liver.

PURPOSE: To propose a simple multicompartment model of the liver and use Bloch-McConnell simulations to demonstrate the effects of iron and fibrosis on shortened-MOLLI (shMOLLI) T1 measurements. Liver T1 values have shown sensitivity to inflammation and fibrosis, but are also affected by hepatic iron content. Modified Look-Locker inversion recovery (MOLLI) T1 measurements are biased by the lower T2 associated with high iron. MATERIALS AND METHODS: A tissue model was generated consisting of liver cells and extracellular fluid (ECF), with iron-dependent relaxation rates. Fibrosis was imitated by increasing the ECF proportion. Simulations of the shMOLLI sequence produced a look-up table (LUT) of shMOLLI-T1 for a given ECF fraction and iron content. The LUT was used to calculate ECF(shMOLLI-T1 ), assuming normal hepatic iron content (HIC), and ECF(shMOLLI- T1,T2*), accounting for HIC determined by T2*, for 77 patients and compared to fibrosis assessed by liver biopsy. RESULTS: Simulations showed that increasing HIC decreases shMOLLI-T1 , with an increase in HIC from 1.0 to 2.5 mg/g at normal ECF fraction decreasing shMOLLI-T1 by 160 msec, while increasing ECF increased ShMOLLI-T1 , with an increase of 20% ECF at normal iron increasing shMOLLI-T1 by 200 msec. Calculated patient ECF(shMOLLI-T1 ) showed a strong dependence on Ishak score (3.3 ± 0.8 %ECF/Ishak stage) and 1/T2* (-0.23 ± 0.04 %ECF/Hz). However, when iron was accounted for to produce ECF(shMOLLI- T1,T2*), it was independent of HIC but retained sensitivity to Ishak score. CONCLUSION: Use of this multicompartment model of the liver with Bloch-McConnell simulation should enable compensation of iron effects when using shMOLLI-T1 to assess fibrosis. LEVEL OF EVIDENCE: 1 J. Magn. Reson. Imaging 2017;45:450-462.

Multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease severity.

BACKGROUND & AIMS: The diagnosis of non-alcoholic steatohepatitis and fibrosis staging are central to non-alcoholic fatty liver disease assessment. We evaluated multiparametric magnetic resonance in the assessment of non-alcoholic steatohepatitis and fibrosis using histology as standard in non-alcoholic fatty liver disease. METHODS: Seventy-one patients with suspected non-alcoholic fatty liver disease were recruited within 1 month of liver biopsy. Magnetic resonance data were used to define the liver inflammation and fibrosis score (LIF 0-4). Biopsies were assessed for steatosis, lobular inflammation, ballooning and fibrosis and classified as non-alcoholic steatohepatitis or simple steatosis, and mild or significant (Activity ≥2 and/or Fibrosis ≥2 as defined by the Fatty Liver Inhibition of Progression consortium) non-alcoholic fatty liver disease. Transient elastography was also performed. RESULTS: Magnetic resonance success rate was 95% vs 59% for transient elastography (P<.0001). Fibrosis stage on biopsy correlated with liver inflammation and fibrosis (rs =.51, P<.0001). The area under the receiver operating curve using liver inflammation and fibrosis for the diagnosis of cirrhosis was 0.85. Liver inflammation and fibrosis score for ballooning grades 0, 1 and 2 was 1.2, 2.7 and 3.5 respectively (P<.05) with an area under the receiver operating characteristic curve of 0.83 for the diagnosis of ballooning. Patients with steatosis had lower liver inflammation and fibrosis (1.3) compared to patients with non-alcoholic steatohepatitis (3.0) (P<.0001); area under the receiver operating characteristic curve for the diagnosis of non-alcoholic steatohepatitis was 0.80. Liver inflammation and fibrosis scores for patients with mild and significant non-alcoholic fatty liver disease were 1.2 and 2.9 respectively (P<.0001). The area under the receiver operating characteristic curve of liver inflammation and fibrosis for the diagnosis of significant non-alcoholic fatty liver disease was 0.89. CONCLUSIONS: Multiparametric magnetic resonance is a promising technique with good diagnostic accuracy for non-alcoholic fatty liver disease histological parameters, and can potentially identify patients with non-alcoholic steatohepatitis and cirrhosis.