Quantification of absolute fat mass using an adipose tissue reference signal model

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Biophysics

Background:

• Accurate quantification of fat mass is crucial for metabolic and cardiovascular health assessment.
• Existing methods for fat mass measurement have limitations in precision and accessibility.
• Magnetic Resonance Imaging (MRI) offers non-invasive potential for body composition analysis.

Purpose of the Study:

• To develop and validate a novel method for quantifying absolute fat mass using MRI.
• To assess the feasibility of this method in ex vivo phantoms and swine specimens at 3 Tesla.
• To establish a reliable, quantitative MRI-based endpoint for fat mass determination.

Main Methods:

• Employed chemical-shift-based fat-water decomposition to generate fat-only images.
• Developed a signal model using reference fat from pure adipose tissue for calibration and normalization.
• Calculated absolute fat mass on a voxel-by-voxel basis and summed across samples.
• Validated the method against independent lipid assay measurements in ex vivo swine tissues.

Main Results:

• The developed MRI method achieved excellent agreement with lipid assay results for absolute fat mass quantification.
• A high correlation (r > 0.99; P < 0.001) was observed, with a small difference of 5% to 7%.
• Demonstrated feasibility in ex vivo swine samples with varying fat and lean tissue compositions.

Conclusions:

• The proposed chemical-shift MRI method enables accurate, quantitative measurement of absolute fat mass.
• The signal model, calibrated with pure adipose tissue reference, enhances precision.
• This technique shows promise as a reliable, non-invasive tool for body composition analysis in research and clinical settings.