肝脏脂肪和铁沉积的准确测量对弥漫性肝病患者的早期诊断和监督治疗具有重要意义。磁共振化学位移编码成像可通过质子密度脂肪分数和R2*（=1/T2*）参数分别反映肝脏中的甘油三酯浓度和铁浓度，但R2*参数测量可能会受脂肪沉积的干扰，两者间生物物理机制和校正关系仍未被完全理解。通过大量临床试验进行验证固然可行，但受磁场强度等诸多因素影响，这势必会耗费巨大的财力、物力、人力和时间。鉴于此，本项目拟开展磁共振R2*参数与肝脏脂肪含量校正关系的仿真方法研究，希望通过虚拟肝脏组织模型的构建，MRI仿真信号的合成与分析，以及临床实验评估优化等方面的深入研究，为理解脂肪对磁共振R2*参数作用机制提供可靠的蒙特卡罗仿真模型。本项目研究有望校正脂肪对磁共振R2*参数的影响，为弥漫性肝病患者肝脏脂肪和铁沉积的准确量化提供可靠依据。

Accurate assessment of hepatic fat and iron overload is vital for early diagnosis and therapy management in patients with diffuse liver diseases. Chemical shift-encoded MRI based proton density fat fraction and R2* (=1/T2*) quantification are promising biomarkers for triglyceride concentration and iron concentration in the liver, however, fat accumulation may be a possible confounder of R2* measurements, the underlying biophysical mechanism between liver fat and R2* is still not understood as well as their relationship. Though large clinical trials can be performed across magnetic field strengths, this would be a tedious and expensive process. The object of this proposal is to develop a numerical simulation approach for R2* relaxivity-fat calibration in the liver MRI. Specifically, this project will explore the effect of fat on R2* by a Monte Carlo model, including virtual liver tissue model, MRI signal synthesis and analysis, and validation by phantom and clinical experiments. In all, this project is expected to correct the effect of fat on R2*, and provide reliable imaging biomarkers for the quantification of liver fat and iron in diffusion liver diseases.