Toward local arterial input functions in dynamic contrast-enhanced MRI.
Toward local arterial input functions in dynamic contrast-enhanced MRI.
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DOI：
10.1002/jmri.22339
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发表时间：
2010-10-01
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通讯作者：
DiBella, Edward V R
中科院分区：
文献类型：
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作者：
Fluckiger, Jacob U;Schabel, Matthias C;DiBella, Edward V R
目的：提出一种基于模型交替最小化 (AMM) 方法在动态对比增强 MRI 扫描中估计局部动脉输入函数 (AIF) 的方法。 材料和方法：该方法将数据子集聚类成代表性曲线，然后将其输入到 AMM 算法以返回参数化的 AIF 和药代动力学参数。计算机模拟用于研究 AMM 能够估计真实 AIF 作为输入组织曲线的函数的准确性。结果：模拟表明，幂律与动力学参数和 SNR 的不确定性以及输入的异质性相关。使用测量的 AIF 计算的动力学参数与使用全局 (P < 0.005) 或局部输入函数 (P = 0.0) 计算的动力学参数显着不同。使用局部 AIF 代替测量的 AIF 会产生平均病变平均参数变化：K(trans)：+24% [+15%，+70%]，k(ep)：+13% [-36%，+300%]。全局估计的输入函数产生平均病变平均变化：K(trans)：+9% [-38%, +65%]，k(ep)：+13% [-100%, +400%]。当使用 Akaike 信息标准考虑额外的自由参数时，观察到的局部 AIF 拟合质量的改善是显着的。结论：局部 AIF 导致显着不同的动力学参数值。拟合质量的统计显着改善表明，使用局部 AIF 进行参数估计的变化反映了基础组织生理学的差异。
PURPOSE: To present a method for estimating the local arterial input function (AIF) within a dynamic contrast-enhanced MRI scan, based on the alternating minimization with model (AMM) method.MATERIALS AND METHODS: This method clusters a subset of data into representative curves, which are then input to the AMM algorithm to return a parameterized AIF and pharmacokinetic parameters. Computer simulations are used to investigate the accuracy with which the AMM is able to estimate the true AIF as a function of the input tissue curves.RESULTS: Simulations show that a power law relates uncertainty in kinetic parameters and SNR and heterogeneity of the input. Kinetic parameters calculated with the measured AIF are significantly different from those calculated with either a global (P < 0.005) or a local input function (P = 0.0). The use of local AIFs instead of measured AIFs yield mean lesion-averaged parameter changes: K(trans): +24% [+15%, +70%], k(ep): +13% [-36%, +300%]. Globally estimated input functions yield mean lesion-averaged changes: K(trans): +9% [-38%, +65%], k(ep): +13% [-100%, +400%]. The observed improvement in fit quality with local AIFs was found to be significant when additional free parameters were accounted for using the Akaike information criterion.CONCLUSION: Local AIFs result in significantly different kinetic parameter values. The statistically significant improvement in fit quality suggests that changes in parameter estimates using local AIFs reflect differences in underlying tissue physiology.