Master of Science
Magnetic Resonance Imaging (MRI) is emerging as a powerful tool to non-invasively evaluate diffuse liver diseases such as hepatic steatosis and iron overload. To test new MRI techniques, phantom studies are utilized in place of patients but often do not consider the microscopic interactions of particles suspended in the media which may cause a notable difference in the signal. Hence, this study investigates the impact of differing particle sizes on the magnetic resonance signal using phantoms. To accomplish this, steatosis phantoms were created using two different mixing methods to control droplet size and while combination iron-fat phantoms featuring iron particles of differing diameters were used to emulate hepatic iron overload. Signal behavior from both sets of phantoms were resolved using linear calibrations to determine values from two known biomarkers, fat fraction and R2*, for steatosis and iron overload, respectively. Overall, evidence showing that particle size impacts the signal to a significant degree remains inconclusive, but fitting model performance in biomarker quantification varied. This study demonstrates different sequencing and post-processing assessments are critical for the analysis of sensitive biomarkers such as R2* and FF.
Dissertation or thesis originally submitted to ProQuest
Brasher, Sarah Caroline, "Impact of Particle Sizes on MRI Signal Relaxation in Phantoms for Assessment of Hepatic Steatosis and Iron Overload" (2023). Electronic Theses and Dissertations. 3125.