Accuracy of fat fraction estimation using Dixon: experimental phantom study
https://doi.org/10.24835/1607-0763-1160
Abstract
Objective. Quantitative assessment of Dixon two-point and three-point technologies operation using phantom modeling in the range from 0 to 70%.
Materials and methods. To simulate substances with different concentrations of the fat phase we chose direct oil-in-water emulsions. Tubes with ready-made emulsions were placed in a phantom. Emulsions based on vegetable oils were presented in the range from 0–70%. The phantom was scanned on an Optima MR450w MRI tomograph (GE, USA) in two Dixon modes: the accelerated two-point method “Lava-Flex” and the three-point method “IDEAL IQ”. A scan was performed on a GEM Flex LG Full RF coil. We calculated fat fraction (FF) using two formulas.
Results. There is a linear relationship of the determined values when calculating the fat concentration in “IDEAL IQ” mode and using the formula based on Water and Fat. The accuracy of body fat percentage measurement in “IDEAL IQ” mode is higher than in “Lava-Flex” mode. According to the MR-sequence “Lava-Flex” draws attention to the overestimation of the measured values of the concentration of fat in relation to the specified values by an average of 57.6% over the entire range, with an average absolute difference of 17.2%.
Conclusion. Using the “IDEAL IQ” sequence, the results of the quantitative determination of fractions by formulas were demonstrated, which are more consistent with the specified values in the phantom. In order to correctly quantify the fat fraction, it is preferable to calculate from the Water and Fat images using Equation 2. Calculations from the In-phase and Out-phase images provide ambiguous results. Phantom modeling with direct emulsions allowed us to detect the shift of the measured fat fraction.
About the Authors
O. Yu. PaninaRussian Federation
Olga Yu. Panina – Junior Scientist Researcher of Technical Monitoring and QA Development Department, Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of Moscow Health Care Department; MD, radiologist, City Clinical Oncological Hospital No. 1 of Moscow Health Care Department; senior laboratory assistant, Moscow State University of Medicine and Dentistry named after A.I. Evdokimov
24, Petrovka str., Moscow 127051;
20/1, Delegatskaya str., Moscow, 127473;
17/1, Baumanskaya str., Moscow 105005
A. I. Gromov
Russian Federation
Alexander I. Gromov – Doct. of Sci. (Med.), Associate Professor; head of the radiation diagnosis and treatment methods, Oncourology Department
20/1, Delegatskaya str., Moscow, 127473
E. S. Akhmad
Russian Federation
Ekaterina S. Akhmad – Scientist Researcher of Technical Monitoring and QA Development
24, Petrovka str., Moscow 127051
A. V. Petraikin
Russian Federation
Alexey V. Petraikin – Cand. of Sci. (Med.), Associate Professor, Senior Researcher of Technical Monitoring and QA Development
24, Petrovka str., Moscow 127051
D. A. Bogachev
Russian Federation
Dmitry A. Bogachev – Head of the laboratory
Moscow region
D. S. Semenov
Russian Federation
Dmitry S. Semenov – Scientist Researcher of Technical Monitoring and QA Development
24, Petrovka str., Moscow 127051
A. V. Vladzymyrskyy
Russian Federation
Anton V. Vladzymyrskyy – Doct. of Sci. (Med.), Associate Professor, Deputy Director for Science
24, Petrovka str., Moscow 127051
Yu. A. Vasilev
Russian Federation
Yury A. Vasilev – Cand. of Sci. (Med.), Director
24, Petrovka str., Moscow 127051
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Review
For citations:
Panina O.Yu., Gromov A.I., Akhmad E.S., Petraikin A.V., Bogachev D.A., Semenov D.S., Vladzymyrskyy A.V., Vasilev Yu.A. Accuracy of fat fraction estimation using Dixon: experimental phantom study. Medical Visualization. 2022;26(4):147-158. https://doi.org/10.24835/1607-0763-1160