Liver fat quantification using a multi‐step adaptive fitting approach with multi‐echo GRE imaging

Zhong, Xiaodong; Nickel, Dominik; Kannengießer, Stephan; Dale, Brian M.; Kiefer, Berthold; Bashir, Mustafa R.

doi:10.1002/mrm.25054

Cited by 191 publications

(198 citation statements)

References 38 publications

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“…[27, 30, 31, 35–38] It acquires multiple echoes at different echo times with fat and water signals nominally in phase or out of phase with each other and applies an algorithm to generate a PDFF parametric map depicting fat quantity and distribution throughout the liver. This method has been shown to reliably measure liver fat content when compared to other magnetic resonance techniques and histology-determined steatosis, and it is sensitive in detecting changes in liver fat content [31, 36, 39] . In order to estimate PDFF across the entire liver, 3 regions of interest (ROIs) 300mm 2 to 400mm 2 in area were placed in each of the nine liver segments on the PDFF parametric maps (figure 1).…”

Section: Methodsmentioning

confidence: 99%

Effect of Weight Loss on Magnetic Resonance Imaging Estimation of Liver Fat and Volume in Patients With Nonalcoholic Steatohepatitis

Patel

Doycheva

Peterson

et al. 2015

Clinical Gastroenterology and Hepatology

145

109

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Background and Aims Little is known about how weight loss affects magnetic resonance imaging (MRI) of liver fat and volume or liver histology in patients with non-alcoholic steatohepatitis (NASH). We measured changes in liver fat and liver volume associated with weight loss using an advanced MRI method. Methods We analyzed data collected from a previous randomized controlled trial, in which 43 adult patients with biopsy-proven NASH underwent clinical evaluation, biochemical tests, and MRI and liver biopsy analyses at the start of the study and after 24 weeks. We compared data between patients who did and did not have at least a 5% decrease in body mass index (BMI) during the study period. Results Ten of 43 patients had at least a 5% decrease in BMI during the study period. These patients had a significant decrease in liver fat, based on MRI proton density fat fraction estimates (18.3% ±7.6 to 13.6% ±13.6, P=0.03)— a relative 25.5% reduction. They also had a significant decrease in liver volume (5.3%). However, no significant changes in levels of alanine aminotransferase or aspartate aminotransferase were observed with weight loss. Thirty-three patients without at least a 5% decrease in BMI had insignificant increases in estimated liver fat fraction and liver volume. Conclusions A reduction in BMI of at least 5% is associated with a significant decrease in liver fat and volume in patients with biopsy-proven NASH. These data should be considered in assessing effect size in studies of patients with non-alcoholic fatty liver disease or obesity that use MRI-estimated liver fat and volume as endpoints.

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Section: Methodsmentioning

confidence: 99%

Effect of Weight Loss on Magnetic Resonance Imaging Estimation of Liver Fat and Volume in Patients With Nonalcoholic Steatohepatitis

Patel

Doycheva

Peterson

et al. 2015

Clinical Gastroenterology and Hepatology

145

109

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“…To address this need, advanced magnetic resonance (MR) imagingbased techniques have been developed to measure the hepatic proton density fat fraction (PDFF) (33)(34)(35)(36)(37)(38)(39)(40); this is a standardized, objective measure of the proportion of the mobile proton density of the liver that is attributable to fat and is emerging as the leading MRbased biomarker of liver fat content (41)(42)(43)(44)(45). In a recent ancillary study from the NASH Clinical Research Network (CRN), Tang and colleagues evaluated the diagnostic performance of an MR imaging-PDFF estimation technique for grading hepatic steatosis in NAFLD by using histopathologic findings as the reference standard (46).…”

Section: Implication For Patient Carementioning

confidence: 99%

Accuracy of MR Imaging–estimated Proton Density Fat Fraction for Classification of Dichotomized Histologic Steatosis Grades in Nonalcoholic Fatty Liver Disease

Tang¹,

Desai²,

Hamilton³

et al. 2015

Radiology

271

216

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Hospital Queens, Queens, NY.q RSNA, 2014 Purpose:To evaluate the diagnostic performance of previously proposed high-specificity magnetic resonance (MR) imaging-estimated proton density fat fraction (PDFF) thresholds for diagnosis of steatosis grade 1 or higher (PDFF threshold of 6.4%), grade 2 or higher (PDFF threshold of 17.4%), and grade 3 (PDFF threshold of 22.1%) by using histologic findings as a reference in an independent cohort of adults known to have or suspected of having nonalcoholic fatty liver disease (NAFLD). Materials andMethods:This prospective, cross-sectional, institutional review boardapproved, HIPAA-compliant single-center study was conducted in an independent cohort of 89 adults known to have or suspected of having NAFLD who underwent contemporaneous liver biopsy. MR imaging PDFF was estimated at 3 T by using magnitude-based low-flip-angle multiecho gradientrecalled-echo imaging with T2* correction and multipeak modeling. Steatosis was graded histologically (grades 0, 1, 2, and 3, according to the Nonalcoholic Steatohepatitis Clinical Research Network scoring system). Sensitivity, specificity, and binomial confidence intervals were calculated for the proposed MR imaging PDFF thresholds. Results:The proposed MR imaging PDFF threshold of 6.4% to diagnose grade 1 or higher steatosis had 86% sensitivity (71 of 83 patients; 95% confidence interval [CI]: 76, 92) and 83% specificity (five of six patients; 95% CI: 36, 100). The threshold of 17.4% to diagnose grade 2 or higher steatosis had 64% sensitivity (28 of 44 patients; 95% CI: 48, 78) and 96% specificity (43 of 45 patients; 95% CI: 85, 100). The threshold of 22.1% to diagnose grade 3 steatosis had 71% sensitivity (10 of 14 patients; 95% CI: 42, 92) and 92% specificity (69 of 75 patients; 95% CI: 83, 97). Conclusion:In an independent cohort of adults known to have or suspected of having NAFLD, the previously proposed MR imaging PDFF thresholds provided moderate to high sensitivity and high specificity for diagnosis of grade 1 or higher, grade 2 or higher, and grade 3 steatosis. Prospective multicenter studies are now needed to further validate these high-specificity thresholds.q RSNA, 2014

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“…Two of the fat peaks cannot be easily distinguished from the water peak, and their contribution to the water peak is corrected using a previously derived liver spectrum. Due to its high sensitivity and accuracy, MRS has been used as a reference standard for a number of studies which have validated the accuracy of MRI-based PDFF 4,5,36,39,46–50 . In some cases, MRS has been used for direct PDFF measurement as a biomarker of hepatic steatosis 8,51,52 .…”

Section: Fat Quantification In the Livermentioning

confidence: 99%

Fat Quantification in the Abdomen

Hong

Dehkordy

Hooker

et al. 2017

Topics in Magnetic Resonance Imaging

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Fatty liver disease is characterized histologically by hepatic steatosis, the abnormal accumulation of lipid in hepatocytes. It is classified into alcoholic fatty liver disease and non-alcoholic fatty liver disease, and is an increasingly important cause of chronic liver disease and cirrhosis. Assessing the severity of hepatic steatosis in these conditions is important for diagnostic and prognostic purposes, as hepatic steatosis is potentially reversible if diagnosed early. The gold standard for assessing hepatic steatosis is liver biopsy, which is limited by sampling error, its invasive nature, and associated morbidity. As such, non-invasive imaging-based methods of assessing hepatic steatosis are needed. Ultrasound and CT are able to suggest the presence of hepatic steatosis based on imaging features, but are unable to accurately quantify hepatic fat content. Since Dixon’s seminal work in 1984, MRI has been used to compute the signal fat fraction from chemical-shift-encoded imaging, commonly implemented as out-of-phase and in-phase imaging. However, signal fat fraction is confounded by several factors that limit its accuracy and reproducibility. Recently, advanced chemical-shift-encoded MRI methods have been developed that address these confounders and are able to measure the proton density fat fraction (PDFF), a standardized, accurate, and reproducible biomarker of fat content. The use of these methods in the liver, as well as in other abdominal organs such as the pancreas, adrenal glands, and adipose tissue will be discussed in this review.

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Liver fat quantification using a multi‐step adaptive fitting approach with multi‐echo GRE imaging

Abstract: This multi-step adaptive fitting approach performed well in both simulated and initial clinical evaluation, and shows potential in the quantification of hepatic steatosis.

Cited by 191 publications

References 38 publications

Effect of Weight Loss on Magnetic Resonance Imaging Estimation of Liver Fat and Volume in Patients With Nonalcoholic Steatohepatitis

Effect of Weight Loss on Magnetic Resonance Imaging Estimation of Liver Fat and Volume in Patients With Nonalcoholic Steatohepatitis

Accuracy of MR Imaging–estimated Proton Density Fat Fraction for Classification of Dichotomized Histologic Steatosis Grades in Nonalcoholic Fatty Liver Disease

Fat Quantification in the Abdomen

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