Search

Author(s): Bonekamp, Susanne; Bonekamp, Susanne; Tang, An; Mashhood, Arian; Wolfson, Tanya; Changchien, Christopher; Middleton, Michael S; Clark, Lisa; Gamst, Anthony; Loomba, Rohit; Sirlin, Claude B | Abstract: PurposeTo describe the spatial distribution of liver fat,using MRI-estimated proton density fat fraction (PDFF), in adults with nonalcoholic fatty liver disease (NAFLD).Materials and methodsThis Investigational Review Board-approved, Health Insurance Portability and Accountability Act-compliant study prospectively enrolled 50 adults (30 women, 20 men) with biopsy-proven NAFLD. Hepatic PDFF was measured by low-flip-angle multiecho spoiled gradient-recalled-echo MRI at 3 Tesla. Three nonoverlapping regions of interest were placed within each liver segment. Statistical analyses included Pearson's correlation, multivariable linear regression, and permutation-based paired tests.ResultsThe study population's mean whole-liver PDFF was 16.1% (range: 1.6–39.6%). The mean whole-liver PDFF variability was 1.9% (range: 0.7–4.5%). Higher variability was associated with higher PDFF (r=0.34;P=0.0156). The mean PDFF was significantly higher in the right lobe than the left (16.5% versus 15.3%, P=0.0028). The mean PDFF variability was higher in the left lobe than the right (1.86% versus 1.28%; Pl0.0001). Segment II had the lowest mean segmental PDFF (14.8%);segment VIII had the highest (16.7%). Segments V(0.71%) and VI (0.70%) had the lowest mean segmental PDFF variability; segment II had the highest (1.32%).ConclusionIN adult NAFLD there are small but significant differences in fat content.

Author(s): Negrete, Lindsey M; Middleton, Michael S; Clark, Lisa; Wolfson, Tanya; Gamst, Anthony C; Lam, Jessica; Changchien, Chris; Deyoung-Dominguez, Ivan M; Hamilton, Gavin; Loomba, Rohit; Schwimmer, Jeffrey; Sirlin, Claude B | Abstract: PurposeTo prospectively describe magnitude-based multi-echo gradient-echo hepatic proton density fat fraction (PDFF) inter-examination precision at 3 Tesla (T).Materials and methodsIn this prospective, Institutional Review Board-approved, Health Insurance Portability and Accountability Act (HIPAA) compliant study, written informed consent was obtained from 29 subjects (body mass indexes g 30 kg/m2). Three 3T MRI examinations were obtained over 75-90 min. Segmental, lobar, and whole liver PDFF were estimated (using three, four, five, or six echoes) by magnitude-based multi-echo MRI in colocalized regions of interest. For estimate (using three, four, five, or six echoes), at each anatomic level (segmental, lobar, whole liver), three inter-examination precision metrics were computed: intra-class correlation coefficient (ICC), standard deviation (SD), and range.ResultsMagnitude-based PDFF estimates using each reconstruction method showed excellent inter-examination precision for each segment (ICC ≥ 0.992; SD ≤ 0.66%; range ≤ 1.24%), lobe (ICC ≥ 0.998; SD ≤ 0.34%; range ≤ 0.64%), and the whole liver (ICC = 0.999; SD ≤ 0.24%; range ≤ 0.45%). Inter-examination precision was unaffected by whether PDFF was estimated using three, four, five, or six echoes.ConclusionMagnitude-based PDFF estimation shows high inter-examination precision at segmental, lobar, and whole liver anatomic levels, supporting its use in clinical care or clinical trials. The results of this study suggest that longitudinal hepatic PDFF change greater than 1.6% is likely to represent signal rather than noise.

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of elevated serum aminotransferase levels in the United States.1–3 It has been estimated that approximately 80 million Americans have NAFLD, and the prevalence of this condition is expected to rise with the continuing epidemic of obesity.4,5 Nonalcoholic steatohepatitis (NASH), which is the progressive form of NAFLD, is typically associated with inflammation and cellular injury in addition to steatosis with or without perisinusoidal fibrosis on liver histology.6 Liver biopsy is the gold standard for diagnosing NAFLD and confirming the presence of NASH.7–9 However, liver biopsy is an invasive procedure and is not routinely favored by general practitioners and patients because of potential risks, which include abdominal pain, bleeding, and, very rarely, death.10 It is not practical to subject all patients with NAFLD to a liver biopsy assessment; therefore, noninvasive biomarkers are needed.11–13 Imaging studies are being increasingly used for noninvasive assessments of NAFLD and have shown promise in detecting hepatic steatosis, but they are limited in their assessment of the presence of NASH. Among the imaging modalities, ultrasound and computed tomography are routinely available and are commonly used, but they lack sensitivity and accuracy in quantifying liver fat.14–16 Magnetic resonance (MR)—especially magnetic resonance spectroscopy (MRS)—has emerged as an accurate technique for quantifying liver fat. However, MRS is limited because it measures a small volume of the sampled tissue and is technically difficult to perform, and it is largely used as a research tool with limited clinical availability and application in routine clinical practice.17,18 Conventional magnetic resonance imaging (MRI) techniques are limited by T1 bias, T(2)* decay, and multifrequency signal-interference effects of protons in fat and eddy currents and, therefore, may not be accurate in the quantification of liver fat.18 Advanced MRI techniques eliminate the biases seen with conventional MRI techniques and can provide the magnetic resonance imaging–estimated proton density fat fraction (MRI-PDFF), a novel biomarker that has shown a robust correlation and equivalency with the magnetic resonance spectroscopy–measured proton density fat fraction (MRS-PDFF).19–22 In addition, MRI-PDFF allows fat mapping of the entire liver and can be applied on any clinical MRI platform, whereas MRS measures fat biochemically in small regions of interest (ROIs). Using a randomized, double-blinded, placebo-controlled clinical trial, we recently showed that MRI-PDFF could detect small amounts of changes in liver fat.23 In the present study, we hypothesized that MRI-PDFF is equivalent to MRS-PDFF in quantifying liver fat cross-sectionally and longitudinally and that the two techniques would correlate with each other over a 24-week time period in patients with biopsy-proven NAFLD. Therefore, we aimed to validate MRI-PDFF by a three-way comparison of the liver MRI-PDFF, MRS-PDFF, and liver histology–determined steatosis grade at two time points (24 weeks apart) and also to assess whether small changes in the liver fat content appreciated by MRI-PDFF have any clinical or biochemical significance.

© 2015, Springer Science+Business Media New York. Purpose: To assess feasibility of and agreement between magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) for estimating hepatic proton density fat fraction (PDFF) in children with known or suspected nonalcoholic fatty liver disease (NAFLD). Materials and methods: Children were included in this study from two previous research studies in each of which three MRI and three MRS acquisitions were obtained. Sequence acceptability, and MRI- and MRS-estimated PDFF were evaluated. Agreement of MRI- with MRS-estimated hepatic PDFF was assessed by linear regression and Bland–Altman analysis. Age, sex, BMI-Z score, acquisition time, and artifact score effects on MRI- and MRS-estimated PDFF agreement were assessed by multiple linear regression. Results: Eighty-six children (61 boys and 25 girls) were included in this study. Slope and intercept from regressing MRS-PDFF on MRI-PDFF were 0.969 and 1.591%, respectively, and the Bland–Altman bias and 95% limits of agreement were 1.17% ± 2.61%. MRI motion artifact score was higher in boys than girls (by 0.21, p = 0.021). Higher BMI-Z score was associated with lower agreement between MRS and MRI (p = 0.045). Conclusion: Hepatic PDFF estimation by both MRI and MRS is feasible, and MRI- and MRS-estimated PDFF agree closely in children with known or suspected NAFLD.

Purpose. To noninvasively assess liver fibrosis using combined-contrast-enhanced (CCE) magnetic resonance imaging (MRI) and texture analysis.Materials and Methods. In this IRB-approved, HIPAA-compliant prospective study, 46 adults with newly diagnosed HCV infection and recent liver biopsy underwent CCE liver MRI following intravenous administration of superparamagnetic iron oxides (ferumoxides) and gadolinium DTPA (gadopentetate dimeglumine). The image texture of the liver was quantified in regions-of-interest by calculating 165 texture features. Liver biopsy specimens were stained with Masson trichrome and assessed qualitatively (METAVIR fibrosis score) and quantitatively (% collagen stained area). UsingL1regularization path algorithm, two texture-based multivariate linear models were constructed, one for quantitative and the other for quantitative histology prediction. The prediction performance of each model was assessed using receiver operating characteristics (ROC) and correlation analyses.Results. The texture-based predicted fibrosis score significantly correlated with qualitative (r=0.698,P<0.001) and quantitative (r=0.757,P<0.001) histology. The prediction model for qualitative histology had 0.814–0.976 areas under the curve (AUC), 0.659–1.000 sensitivity, 0.778–0.930 specificity, and 0.674–0.935 accuracy, depending on the binary classification threshold. The prediction model for quantitative histology had 0.742–0.950 AUC, 0.688–1.000 sensitivity, 0.679–0.857 specificity, and 0.696–0.848 accuracy, depending on the binary classification threshold.Conclusion. CCE MRI and texture analysis may permit noninvasive assessment of liver fibrosis.

PurposeTo explore the cross-sectional and longitudinal relationships between fractional liver fat content, liver volume, and total liver fat burden.MethodsIn 43 adults with non-alcoholic steatohepatitis participating in a clinical trial, liver volume was estimated by segmentation of magnitude-based low-flip-angle multiecho GRE images. The liver mean proton density fat fraction (PDFF) was calculated. The total liver fat index (TLFI) was estimated as the product of liver mean PDFF and liver volume. Linear regression analyses were performed.ResultsCross-sectional analyses revealed statistically significant relationships between TLFI and liver mean PDFF (R 2 = 0.740 baseline/0.791 follow-up, P < 0.001 baseline/P < 0.001 follow-up), and between TLFI and liver volume (R 2 = 0.352/0.452, P < 0.001/< 0.001). Longitudinal analyses revealed statistically significant relationships between liver volume change and liver mean PDFF change (R 2 = 0.556, P < 0.001), between TLFI change and liver mean PDFF change (R 2 = 0.920, P < 0.001), and between TLFI change and liver volume change (R 2 = 0.735, P < 0.001).ConclusionLiver segmentation in combination with MRI-based PDFF estimation may be used to monitor liver volume, liver mean PDFF, and TLFI in a clinical trial.

To describe the spatial distribution of liver fat,using MRI-estimated proton density fat fraction (PDFF), in adults with nonalcoholic fatty liver disease (NAFLD).This Investigational Review Board-approved, Health Insurance Portability and Accountability Act-compliant study prospectively enrolled 50 adults (30 women, 20 men) with biopsy-proven NAFLD. Hepatic PDFF was measured by low-flip-angle multiecho spoiled gradient-recalled-echo MRI at 3 Tesla. Three nonoverlapping regions of interest were placed within each liver segment. Statistical analyses included Pearson's correlation, multivariable linear regression, and permutation-based paired tests.The study population's mean whole-liver PDFF was 16.1% (range: 1.6–39.6%). The mean whole-liver PDFF variability was 1.9% (range: 0.7–4.5%). Higher variability was associated with higher PDFF (r=0.34;P=0.0156). The mean PDFF was significantly higher in the right lobe than the left (16.5% versus 15.3%, P=0.0028). The mean PDFF variability was higher in the left lobe than the right (1.86% versus 1.28%; P0.0001). Segment II had the lowest mean segmental PDFF (14.8%);segment VIII had the highest (16.7%). Segments V(0.71%) and VI (0.70%) had the lowest mean segmental PDFF variability; segment II had the highest (1.32%).IN adult NAFLD there are small but significant differences in fat content.

Bile acid sequestrants (BAS) lower plasma low density lipoprotein levels and improve glycemic control. Colestimide, a BAS, has been claimed by computed tomography to reduce liver fat. Therefore, we examined the efficacy of colesevelam, a potent BAS, to decrease liver fat in patients with biopsy-proven nonalcoholic steatohepatitis (NASH). Liver fat was measured by a novel magnetic resonance imaging (MRI) technique, the proton-density-fat-fraction (PDFF), as well as by conventional MR spectroscopy (MRS). Fifty patients with biopsy-proven NASH were randomly assigned to either colesevelam 3.75 g/day orally or placebo for 24 weeks. The primary outcome was change in liver fat as measured by MRI-PDFF in colocalized regions of interest within each of the nine liver segments. Compared with placebo, colesevelam increased liver fat by MRI-PDFF in all nine segments of the liver with a mean difference of 5.6% (P = 0.002). We cross-validated the MRI-PDFF-determined fat content with that assessed by colocalized MRS; the latter showed a mean difference of 4.9% (P = 0.014) in liver fat between the colesevelam and the placebo arms. MRI-PDFF correlated strongly with MRS-determined hepatic fat content (r2= 0.96, P < 0.0001). Liver biopsy assessment of steatosis, cellular injury, and lobular inflammation did not detect any effect of treatment. Conclusion: Colesevelam increases liver fat in patients with NASH as assessed by MRI as well as MRS without significant changes seen on histology. Thus, MRI and MRS may be better than histology to detect longitudinal changes in hepatic fat in NASH. Underlying mechanisms and whether the small MR-detected increase in liver fat has clinical consequences is not known. © 2012 American Association for the Study of Liver Diseases.

A S L D A b st ra ct s correlation was observed between PI signal and fibrosis scores (r = 0.33; p = 0.04). When patients were stratified according to their liver parenchyma PI signal, a significant difference was achieved between patients with Ishak score 1-2 vs 3-5 (p = 0.01). The median DI was 0.39 ± 0.15 (0.17 0.61); because DI is given by the ratio between the minimum velocity/ maximum velocity of downward HV flow, with higher DI, HV waveforms tended to become abnormal (r = 0.7, p = 0.01). All patients with Ishak > 3 had an abnormal hepatic vein waveform; DI > 0.45 was significantly more likely to be seen in patients with Ishak > 3. Conclusions: We report preliminary results suggesting that CEUS with software-based quantitative analysis in addition to standard Doppler indices may provide a useful noninvasive tool in assessing the severity of liver fibrosis in a clinical setting.