Abstract
PURPOSE: To investigate the impact of iron particle size on R2* and fat fraction (FF) estimations for coexisting hepatic iron overload and steatosis condition using Monte Carlo simulations and phantoms. METHODS: Three iron particle sizes (0.38, 0.52, and 0.71 μm) were studied using simulations and phantoms. Virtual liver models mimicking in vivo spatial distribution of fat droplets and iron deposits were created, and MRI signals were synthesized using Monte Carlo simulations for FF 1%-30% and liver iron concentration (LIC) 1-20 mg/g. Seventy-five fat-iron phantoms with varying iron (0-8 μg/mL) and fat (0%-40%) concentrations and particle sizes were constructed. Three-way analysis of variance was used to assess the effect of iron particle size on R2* and FF estimations. RESULTS: In simulations, estimated and true FF were in excellent agreement (slope: 0.93-1.09) for liver iron concentration ≤ 13 mg/g. For both simulations and phantoms, FF estimation bias increased as iron concentration increased and particle size decreased, with 0.71μm iron particle having the lowest bias (≤ 20%), and 0.52 μm and 0.38 μm iron particles producing higher bias (≥ 20%) for higher iron concentrations and lower FFs. Additionally, R2* increased linearly with increasing iron concentration (r ≥ 0.87) and decreasing particle size. Iron particle size significantly influenced the estimated versus true FF (simulations: p = 0.04; phantoms: p = 0.03) and R2* -iron concentration (simulations: p < 0.001; phantoms: p < 0.01) relationships. Heatmap demonstrated broader region with higher FF estimation bias as iron particle size decreased, especially at higher iron concentration. CONCLUSION: R2* and FF estimations are affected by iron particle size, with smaller particles leading to higher R2* values and increased FF estimation bias.