POSTER PRESENTATIONS imaging Centre at Cheadle (UK) using Siemens 1.5T MAGNETOM Aera, syngo MR D13 using a multi-echo spoiled-gradient-echo. MR data were analysed using LiverMultiScan software and proton density fat fraction (PDFF) obtained. Comparison between groups was tested using Kruskal-Wallis and Kolmogorov-Smirnov (KS) tests. Regression analysis was performed against log-transformed PDFF. Results: The high-throughput abdominal MRI protocol used for obtaining PDFF in the UKBiobank proved robust and reproducible, with 97.6% scans successfully analysed. The cohort had a median BMI of 26.09 kg/m2 (range 16.04–48.84 kg/m2), and median age of 62 years (range 45–73 years). 91.6% of subjects were Caucasian. The overall hepatic fat distribution (see Figure) was centred between 1–2%, but highly-skewed to the right, with a mean liver fat of 4.08%, and median of 2.10%. 20.2% of individuals had >5.5% liver fat, the commonly accepted risk level. 90% of participants with a PDFF > 5% had a BMI > 25 kg/m2. There was a strong relationship between both liver fat and BMI ( p < 2e−16); and between liver fat and age ( p < 8.71e −06). Females had significantly lower liver fat than males (one-sided K-S test, p = 10e−29). There was also a significant relationship between liver fat and self-reported factors including diabetes, weightloss, and hypertension. Regression analysis showed that BMI had the strongest effect on liver fat, followed by gender, diabetes, hypertension, age and self-reported weight gain.
those obtained in a meta-analysis of two prospective clinical trials with biopsy-proven high-risk NAFLD patients (NASH or >F1 fibrosis). Results: In the unselected population sample, 20.7% had steatosis (>5% PDFF), in agreement with UK population estimates (Preiss & Sattar, 2008). In the reference NAFLD cohort, 74.5% had PDFF >5% (mean PDFF 12.64%). The mean LIF score in the high-risk NASH cohort was 2.70 (s.d. 0.80). A LIF score >2 is associated with a higher likelihood of high-risk NAFLD and liver-related clinical outcomes (Pavlides et al., 2016). In the unselected group, LIF ranged from 0 to 3.4 with a mean of 0.96, (s.d. 0.42). In a plot of LIF vs PDFF, the high-risk NAFLD cohort can be used to define the upper right quadrant (PDFF > 5% and LIF > 2). 94 (1.8%) of the unselected cohort occupy the highrisk NAFLD quadrant.
Conclusions: High throughput imaging can identify patients with high risk NASH + fibrosis, and this imaging technique can be used to identify at risk patients from a general population by screening. This is of tremendous value as an enrichment tool for clinical trials. Conclusions: The proportion of subjects (20.2%) with >5.5% PDFF was slightly lower than previously reported in the UK population 26.4%. The 95th percentile for participants with BMI < 25 kg/m2 was 5.40%, in agreement with the widely accepted value. Hepatic steatosis is strongly associated with diabetes and metabolic syndrome. Participants with PDFF < 5.5% and a BMI < 25 kg/m2 were half as likely to have hypertension, and one-quarter as likely to have diabetes. THU-500 Predicted prevalence and stratification of non-alcoholic fatty liver disease in a large population using non-invasive multiparametric MRI H. Wilman1,2, M. Kelly2, A. Dennis2, C. Kelly2, L. Thomas1, S. Neubauer2,3, J. Bell1, R. Banerjee2. 1Life Sciences, University of Westminster, London; 2Perspectum Diagnostics; 3OCMR, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom E-mail:
[email protected] Background and Aims: To determine the suitability of multiparametric MRI of the liver for the assessment and stratification of NAFLD in large populations. Methods: 3718 individuals underwent multiparametric MRI, per the LiverMultiScan protocol, as a part of the UKBiobank imaging study. Liver disease status was unknown. Estimates of liver fat fraction (PDFF %) and fibroinflammatory disease (LIF score) were calculated using LiverMultiScan software. Population statistics were compared to
THU-501 Novel mapping of fibrosis and hepatic inflammation in NASH patients with dual R2 MRI relaxometry H.M.L. Filho1, W. Chua-anusorn2, C.P. Oliveira3, F.J. Carrilho3, F. Lima4, V. Alves4, P. Clark2, M. Rocha1. 1Department of Radiology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil; 2MagnePath, Perth, Australia; 3Department of Gastroenterolgy; 4Department of Pathology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil E-mail:
[email protected] Background and Aims: Quantitative MRI (QMRI) techniques for measuring liver iron and fat have been validated. However, evaluation of hepatic inflammation and fibrosis is a challenge, being important for patient stratification and treatment. Our objective is to evaluate a QMRI multi-component relaxometry (MCR) technique to map fibrosis and inflammation in patients with non-alcoholic steatohepatitis (NASH). The extracellular water fraction (ECWF) was investigated for fibrosis, and the ratio of the transverse relaxation rate (R2) between intra and extra-cellular water (R2I/E) was assessed for inflammation. Methods: 105 NASH diagnosed patients with liver biopsy were selected within 6 months for MRI exam. We used a 3T Philips Achieva with a multi-spin echo (MSE) sequence for determining extracellular water fraction and R2 maps. Scan time was ∼8 minutes. The images was analysed by a radiologist and physicist with over 12 years experience each in abdominal imaging. The biopsies were reviewed by a pathologist with 14 years of liver experience using the NASHCRN score.
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POSTER PRESENTATIONS In total, 53 paired biopsy and MRI results were available at submission. 9 volunteers with normal lab results and no known liver disease were used for control. Results: The mean extracellular water fraction (ECWF) for the 53 NASH patients was 25.7 ( ± 4.1)%, and for the 9 healthy volunteers the mean ECWF was 17.6 ( ± 2.7)%. There was a significant correlation between ECWF and fibrosis stage (rs = 0.79, p < 1.0−06). For distinction between heathy and F1 patients we achieved an AUROC of 0.99, sensitivity of 95% and specificity of 98% at a threshold ECWF of 20.7%. We could differentiate almost all classes of fibrosis ( p < 0.05), with the exception of F3 to F4 ( p = 0.077), but only 5 F4 patients have been included to date. The mean intra to extra-cellular transverse relaxation rate ratio (R2I/E) for the 53 NASH patients was 3.4 ( ± 0.8), and 2.4 ( ± 0.1) for the 9 healthy volunteers. For distinction of normal parenchyma from mild lobular inflammation we achieved an AUROC of 0.96, sensitivity of 91% and specificity of 91% at an R2i/E threshold of 2.7.
Background and Aims: The relationship between nonalcoholic fatty liver disease (NAFLD), obesity, insulin resistance, and hyperferritinemia is well established. The association of metabolic syndrome and hyperferritinemia is called dysmetabolic iron overload syndrome (DIOS). The hyperferritinemia in these patients may reflect the inflammatory status of NAFLD patients and obesity, but 33% reflects liver iron overload where iron in hepatocytes results in worse prognosis. The gold standard for iron overload is liver biopsy, but noninvasive approaches using magnetic resonance imaging (MRI) are now showing greater sensitivity. Our aim is to compare the iron content in liver biopsy of NASH patients with quantitative MRI (QMRI) separating hemosiderosis from steatosis. Methods: The sample of 51 NASH diagnosed patients with liver biopsy had 26 with hyperferritinemia and 25 without. The patients were selected if biopsy was done within 6 months of MRI. Magnitude MRI data was acquired on a 3T Philips Achieva with a spoiled multi-gradient echo (SPMGE) sequence for determining fat fraction and water R2* (R2*W). The results were compared with the ferritin levels and the iron in biopsy. The MRI exams were analyzed by a radiologist with 12 years of abdominal imaging experience. A pathologist with 14 years of experience with liver pathology revised the specimens. Results: DIOS frequency was 35%. Mean ferritin levels were 375( ± 333,7) ng/dL. These levels correlated well with scored liver iron content ( p < 0,001) The ferritin level capable to distinguish iron overload was 284.5 ng/dL (sensitivity of 83%, specificity 72.7%). The MRI also correlated well with all scores of hepatic iron overload in the sample ( p < 0,001). We did not have any NASH patient with a score 3 iron overload. Absence of siderosis from mild iron overload was distinguished with a R2*W cutoff level of 64.5 s−1. We also found a good correlation between ferritin levels and R2*W even in the absence of siderosis in the biopsy ( p < 0,005).
Conclusions: QMRI with dual R2 relaxometry showed good results in this preliminary analysis for measuring liver fibrosis and inflammation, especially in the early stages for NASH patients. The results are consistent with fibrosis increasing the proportion of the extracellular space, and with inflammation lowering extra-cellular R2 values relative to intra-cellular R2. THU-502 Hepatic iron overload analysis bymagnetic resonance imaging in a non-alcoholic fatty liver disease population H.M.L. Filho1, P. Fabrega2, W. Chua-anusorn3, C.P. Oliveira4, F.J. Carrilho4, F. Lima5, C. Cercato2, P. Clark3, M. Rocha1. 1Department of Radiology; 2Department of Endocrinology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil; 3MagnePath, Perth, Australia; 4 Department of Gastroenterology; 5Department of Pathology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil E-mail:
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