title: Quantification of liver fat: A comprehensive review.
abstract: Fat accumulation in the liver causes metabolic diseases such as obesity, hypertension, diabetes or dyslipidemia by affecting insulin resistance, and increasing the risk of cardiac complications and cardiovascular disease mortality. Fatty liver diseases are often reversible in their early stage; therefore, there is a recognized need to detect their presence and to assess its severity to recognize fat-related functional abnormalities in the liver. This is crucial in evaluating living liver donors prior to transplantation because fat content in the liver can change liver regeneration in the recipient and donor. There are several methods to diagnose fatty liver, measure the amount of fat, and to classify and stage liver diseases (e.g. hepatic steatosis, steatohepatitis, fibrosis and cirrhosis): biopsy (the gold-standard procedure), clinical (medical physics based) and image analysis (semi or fully automated approaches). Liver biopsy has many drawbacks: it is invasive, inappropriate for monitoring (i.e., repeated evaluation), and assessment of steatosis is somewhat subjective. Qualitative biomarkers are mostly insufficient for accurate detection since fat has to be quantified by a varying threshold to measure disease severity. Therefore, a quantitative biomarker is required for detection of steatosis, accurate measurement of severity of diseases, clinical decision-making, prognosis and longitudinal monitoring of therapy. This study presents a comprehensive review of both clinical and automated image analysis based approaches to quantify liver fat and evaluate fatty liver diseases from different medical imaging modalities.
authors.affiliation: Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, USA. Electronic address: goceri.1@osu.edu.
authors.forename: Evgin
authors.initials: E
authors.lastname: Goceri
authors.affiliation: Department of Radiology, Wexner Medical Center, The Ohio State University, Columbus, USA.
authors.forename: Zarine K
authors.initials: ZK
authors.lastname: Shah
authors.affiliation: Department of Radiology, Wexner Medical Center, The Ohio State University, Columbus, USA.
authors.forename: Rick
authors.initials: R
authors.lastname: Layman
authors.affiliation: Department of Radiology, Wexner Medical Center, The Ohio State University, Columbus, USA.
authors.forename: Xia
authors.initials: X
authors.lastname: Jiang
authors.affiliation: Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, USA.
authors.forename: Metin N
authors.initials: MN
authors.lastname: Gurcan
mesh_terms: D015415:Biomarkers / Q000378:metabolism; D001706:Biopsy; D005234:Fatty Liver / Q000378:metabolism / Q000473:pathology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000378:metabolism / Q000473:pathology; D008103:Liver Cirrhosis / Q000378:metabolism / Q000473:pathology; D008297:Male
chemical_list: D015415:Biomarkers
keywords: Biopsy; CT; Fatty liver diseases; Liver fat quantification; MR; Steatosis; US