Relaxivity-iron calibration in hepatic iron overload: Reproducibility and extension of a Monte Carlo model.
Relaxivity-iron calibration in hepatic iron overload: Reproducibility and extension of a Monte Carlo model.
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利用蒙特卡罗模型再现肝铁过载时的弛豫铁校准，并利用多自旋回波（MSE）成像进一步扩展该模型。如前所述，弛豫速率（和单自旋回波R2）与肝铁浓度（LIC）之间的关系可以通过蒙特卡罗模型来表征，该模型结合了真实的肝脏结构、铁分布和质子迁移率。本研究采用蒙特卡罗模型模拟了1.5T和3.0T时的弛豫铁校准曲线。此外，该模型扩展了MSE成像，并使用两种不同的拟合模型进行铁校准评估：具有恒定偏移的单指数模型和非单指数模型。结果与以往的经验校准和蒙特卡罗预测一致，准确地再现了弛豫铁校准。在1.5T和3.0T下，预测和单自旋回波R2分别增加了2.00和1.51倍。MSE信号及其对应的R2强烈依赖于LIC、回波间时间和场强。初步结果表明，非单指数模型准确表征了模拟的MSE信号，预测的弛豫参数与LIC之间存在较强的相关性。利用所提出的蒙特卡罗模型，弛豫铁校准是可重复的。此外，该模型可以很容易地扩展到其他重要的应用，包括预测MSE成像的信号行为。
To reproduce relaxivity-iron calibration in hepatic iron overload using a Monte Carlo model, and further extend the model with multiple spin echo (MSE) imaging. As previously reported, relationships between relaxation rates (and single spin echo R2) and liver iron concentration (LIC) can be characterized by a Monte Carlo model incorporating realistic liver structure, iron distribution, and proton mobility. In this study, relaxivity-iron calibration curves at 1.5T and 3.0T were simulated using the Monte Carlo model. Furthermore, the model was extended with MSE imaging, and iron calibrations were evaluated using two different fitting models: mononexponential with a constant offset and non-monoexponential. Results consistent with previous empirical calibrations and Monte Carlo predictions were accurately reproduced for relaxivity-iron calibration. The predicted and single spin echo R2 increased by a factor of 2.00 and 1.51, respectively, at 1.5T versus 3.0T. MSE signals and their corresponding R2 depended strongly on LIC, inter-echo time, and field strength. Preliminary results showed that a non-monoexponential model accurately characterizes the simulated MSE signals, and that strong correlations were found between predicted relaxation parameters and LIC. Relaxivity-iron calibration is reproducible using the proposed Monte Carlo model. Furthermore, this model can be readily extended to other important applications, including predicting signal behavior for MSE imaging.