Pathologic Assessment of Non-alcoholic Fatty Liver Disease

Bondini, Silvia; Kleiner, David E.; Goodman, Zachary; Gramlich, Terry L.; Younossi, Zobair M.

doi:10.1016/j.cld.2007.02.002

Cited by 64 publications

(41 citation statements)

References 11 publications

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“…Grades 2 and 3 were combined for statistical analysis (high grade) and grade 1 (low grade). Fibrosis was assessed with the Masson trichome stain [9]. Other histological features evaluated in hematoxylin-eosin sections included lobulillar inflammation and portal inflammation.…”

Section: Liver Biopsymentioning

confidence: 99%

Influence of Visfatin on Histopathological Changes of Non-alcoholic Fatty Liver Disease

et al. 2008

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The mean age was 42.8 +/- 11.2 years, the mean BMI was 33.1 +/- 10.2 with 37 males (67.3%) and 18 females (32.7%). Probabilities to have; portal inflammation increased 1.11 (CI95%:1.03-1.50) with each increment of 1 ng/ml of visfatin concentration, high grade of steatosis increased 1.25 (CI 95%:1.06-1.61) with each unit of insulin concentrations, fibrosis increased 1.12 (CI 95%:1.02-1.43) with each unit of fat mass and lobulillar inflammation increased 13.4 (CI 95%:1.3-147) with each unit of HOMA-IR. Portal inflammation frequencies were different between groups (low visfatin group 13.07 < ng/ml: 37.5% versus high visfatin group 13.07 > ng/ml: 62.5%; P < 0.05). In conclusion, several histopathological changes in liver biopsies could be explained by insulin concentrations, HOMA-IR, and fat mass amount. Moreover, visfatin plasma concentrations could predict the presence of portal inflammation in NAFLD patients.

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Section: Liver Biopsymentioning

confidence: 99%

Influence of Visfatin on Histopathological Changes of Non-alcoholic Fatty Liver Disease

et al. 2008

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“…Currently, the reference standard for the diagnosis and grading of steatosis is biopsy. However, widespread use of biopsy is limited because it is expensive, invasive, and has high sampling error (13)(14)(15). Steatosis is heterogeneous, and the sampling error likely refl ects the inherent fl aw of attempting to characterize a heterogeneous disease with a sample of only 1/50 000 of the liver.…”

Section: Patientsmentioning

confidence: 99%

“…Comparison with a single targeted biopsy is unlikely to provide adequate validation because it is well known that biopsy suffers from marked sampling variability (13)(14)(15). In addition, core biopsies are used for histologic analysis, and pathologic grading of steatosis is based on the number of cells with intracellular fat rather than actual triglyceride correlation.…”

Section: Gastrointestinal Imaging: Quantifi Cation Of Hepatic Steatosismentioning

confidence: 99%

Quantification of Hepatic Steatosis with T1-independent, T2*-corrected MR Imaging with Spectral Modeling of Fat: Blinded Comparison with MR Spectroscopy

Meisamy

Hines²,

Hamilton³

et al. 2011

Radiology

353

412

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Purpose:To prospectively compare an investigational version of a complex-based chemical shift-based fat fraction magnetic resonance (MR) imaging method with MR spectroscopy for the quantifi cation of hepatic steatosis. Materials and Methods:This study was approved by the institutional review board and was HIPAA compliant. Written informed consent was obtained before all studies. Fifty-fi ve patients (31 women, 24 men; age range, 24-71 years) were prospectively imaged at 1.5 T with quantitative MR imaging and single-voxel MR spectroscopy, each within a single breath hold. The effects of T2* correction, spectral modeling of fat, and magnitude fi tting for eddy current correction on fat quantifi cation with MR imaging were investigated by reconstructing fat fraction images from the same source data with different combinations of error correction. Single-voxel T2-corrected MR spectroscopy was used to measure fat fraction and served as the reference standard. All MR spectroscopy data were postprocessed at a separate institution by an MR physicist who was blinded to MR imaging results. Fat fractions measured with MR imaging and MR spectroscopy were compared statistically to determine the correlation ( r 2 ), and the slope and intercept as measures of agreement between MR imaging and MR spectroscopy fat fraction measurements, to determine whether MR imaging can help quantify fat, and examine the importance of T2* correction, spectral modeling of fat, and eddy current correction. Two-sided t tests (signifi cance level, P = .05) were used to determine whether estimated slopes and intercepts were signifi cantly different from 1.0 and 0.0 , respectively. Sensitivity and specifi city for the classifi cation of clinically signifi cant steatosis were evaluated. Results:Overall, there was excellent correlation between MR imaging and MR spectroscopy for all reconstruction combinations. However, agreement was only achieved when T2* correction, spectral modeling of fat, and magnitude fi tting for eddy current correction were used ( r 2 = 0.99; slope 6 standard deviation = 1.00 6 0.01, P = .77; intercept 6 standard deviation = 0.2% 6 0.1, P = .19 ). Conclusion:T1-independent chemical shift-based water-fat separation MR imaging methods can accurately quantify fat over the entire liver, by using MR spectroscopy as the reference standard, when T2* correction, spectral modeling of fat, and eddy current correction methods are used.q RSNA, 2011

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“…Patients with the following conditions were excluded: a history of drinking alcohol and coffee; those with various types of viral hepatitis or familial hyperlipidemia (HLP); those being treated with drugs that can increase ALT, AST and GGT, also antihypertensive drugs, immunosuppressive agents; those with hormone, heart, brain, or kidney diseases; those with liver disease, storage disease, acute or temporary illness, autoimmune liver disease, Wilson disease, α-1 antitrypsin deficiency, malignant liver tumors, infections and biliary tract diseases (Bondini et al, 2007).…”

Section: Exclusion Criteriamentioning

confidence: 99%

Large-scale analysis of factors influencing nonalcoholic fatty liver disease and its relationship with liver enzymes

Chen

Shi

et al. 2014

Genet. Mol. Res.

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ABSTRACT. Serum liver enzyme levels are often used effectively for the evaluation of nonalcoholic fatty liver disease (NAFLD). We aimed to investigate the associations between serum liver enzyme levels and risks for NAFLD in over 8000 cases in a large-scale analysis. A cross-sectional survey with multiple stages and random samplings was performed from May 2007 to May 2009 on 8102 workers at Tongji University. A questionnaire was given, assessments of physical measurements, plasma glucose, lipid profiles, and liver enzymes were made, and real-time liver ultrasounds conducted. The prevalence of NAFLD in Tongji University was 22.2%. It was higher in males than in females (P = 0.0023). The body mass index, waist-to-hip ratio, serum total triglycerides, serum total cholesterol, alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transferase (GGT) values were all higher in the NAFLD group than in the control group. For moderate and severe NAFLD patients, the ALT, AST and GGT values were significantly Factors influencing nonalcoholic fatty liver disease increased, high density lipoprotein cholesterol was decreased, and drinking much, heavy entertainment and less exercise were more prevalent (P < 0.001). There were strong correlations between serum liver enzyme levels and NAFLD (P < 0.001), with GGT being a more sensitive marker for NAFLD than ALT or AST. ALT and GGT were independent predictors for NAFLD, and GGT was a better predictor than ALT for NAFLD.

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Pathologic Assessment of Non-alcoholic Fatty Liver Disease

Cited by 64 publications

References 11 publications

Influence of Visfatin on Histopathological Changes of Non-alcoholic Fatty Liver Disease

Influence of Visfatin on Histopathological Changes of Non-alcoholic Fatty Liver Disease

Quantification of Hepatic Steatosis with T1-independent, T2*-corrected MR Imaging with Spectral Modeling of Fat: Blinded Comparison with MR Spectroscopy

Large-scale analysis of factors influencing nonalcoholic fatty liver disease and its relationship with liver enzymes

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