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Obesity (Silver Spring) ; 17(12): 2239-44, 2009 Dec.
Article in English | MEDLINE | ID: mdl-19461588

ABSTRACT

An abundance of fat stored within the liver, or steatosis, is the beginning of a broad hepatological spectrum, usually referred to as fatty liver disease (FLD). For studies on FLD, quantitative hepatic fat ultrasonography would be an appealing study modality. Objective of this study was to develop a technique for quantifying hepatic fat content by ultrasonography and validate this using proton magnetic resonance spectroscopy ((1)H MRS) as gold standard. Eighteen white volunteers (BMI range 21.0-42.9) were scanned by both ultrasonography and (1)H MRS. Altered ultrasound characteristics, present in the case of FLD, were assessed using a specially developed software program. Various attenuation and textural based indices of FLD were extracted from ultrasound images. Using linear regression analysis, the predictive power of several models (consisting of both attenuation and textural based measures) on log 10-transformed hepatic fat content by (1)H MRS were investigated. The best quantitative model was compared with a qualitative ultrasonography method, as used in clinical care. A model with four ultrasound characteristics could modestly predict the amount of liver fat (adjusted explained variance 43.2%, P = 0.021). Expanding the model to seven ultrasound characteristics increased adjusted explained variance to 60% (P = 0.015), with r = 0.789 (P < 0.001). Comparing this quantitative model with qualitative ultrasonography revealed a significant advantage of the quantitative model in predicting hepatic fat content (P < 0.001). This validation study shows that a combination of computer-assessed ultrasound measures from routine ultrasound images can be used to quantitatively assess hepatic fat content.


Subject(s)
Adipose Tissue/diagnostic imaging , Fatty Liver/diagnostic imaging , Liver/diagnostic imaging , Obesity/diagnostic imaging , Adult , Body Mass Index , Fatty Liver/diagnosis , Fatty Liver/pathology , Female , Humans , Image Interpretation, Computer-Assisted , Liver/pathology , Magnetic Resonance Spectroscopy/methods , Male , Middle Aged , Models, Biological , Obesity/pathology , Software , Ultrasonography/methods , Young Adult
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