Related Experiment Video
Updated: Mar 11, 2026

Fat-Water Phantoms for Magnetic Resonance Imaging Validation: A Flexible and Scalable Protocol
Published on: September 7, 2018
Accuracy analysis of intrahepatic fat density measurements using dual-energy computed tomography: Validation using a
Tomohiro Arai1,2, Masaki Misawa3, Miki Arai1
1Department of Radiology, Center Hospital of the National Center to Global Health and Medicine, Tokyo, Japan.
Background:
Currently, no standardized method for measuring intrahepatic fat density via conventional computed tomography (CT) exists.
Objective:
We aim to quantify intrahepatic fat density via material decomposition analysis using rapid kilovolt peak-switching dual-energy (RSDE) CT.
Methods:
Homogenized porcine liver and fat (lard) were mixed in various ratios to produce phantoms for fat density verification. The actual fat density was measured on the basis of the phantom volume and weight, and these measurements were used as reference densities. The fat and liver mass attenuation coefficients, which were used as the material basis pairs, were employed in the material decomposition analysis. Then, the measured fat density of each phantom was compared with the reference densities.
Results:
For fat content differences exceeding 2%, the measured fat density for the phantoms became statistically significant (p < 0.01). The correlation between the reference densities and RSDE-measured fat densities was reasonably high (R > 0.9997); this indicates the validity of this analysis method.
Conclusions:
Intrahepatic fat density can be measured using the mass attenuation coefficients of fat and liver in a material decomposition analysis. Given the knowledge of the accuracy and the limitations found in this study, our method can quantitatively evaluate fat density.
More Related Videos
08:41Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease
Published on: March 24, 2023
05:37Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI
Published on: October 20, 2023