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Analysis of the effects of fitting errors of DCE-CT signals on perfusion parameters

机译:DCE-CT信号拟合误差对灌注参数的影响分析

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Computed Tomography perfusion (CTp) is a promising technique for estimating perfusion parameters, by analysing Time Concentration Curves (TCCs) of the administered contrast agent. However, several artefacts can degrade the signal quality, jeopardizing quantitative measurements. Despite different methods exploit TCCs to compute perfusion parameters, none of them has investigated how TCC fitting errors may affect final perfusion values. The first goal of this work is to investigate residuals distributions in significant signal's portions, then relating them to Blood Flow (BF). The Gamma Variate (GV) function is addressed to fit TCCs. Voxel-based BF is computed with the two most spread methods in literature, Maximum Slope (MS) and Deconvolution (DV). Experimental results prove that residuals coming from a Gaussian distribution yield percent errors maps locally smooth, thus attaining residuals-independent BF values. Besides results, the methodological approach can be spent in future researches in order to encourage CTp reproducibility.
机译:通过分析所给予造影剂的时间浓度曲线(TCC),计算机断层扫描灌注(CTp)是一种用于估算灌注参数的有前途的技术。但是,一些伪影会降低信号质量,从而危及定量测量。尽管有不同的方法利用TCC计算灌注参数,但是他们都没有研究TCC拟合误差如何影响最终的灌注值。这项工作的第一个目标是研究重要信号部分中的残差分布,然后将其与血流(BF)相关联。伽玛变量(GV)功能已解决以适合TCC。基于体素的BF是使用文献中两种分布最广的方法进行计算的,即最大斜率(MS)和解卷积(DV)。实验结果证明,来自高斯分布的收益率误差百分比残差映射局部平滑,从而获得了与残差无关的BF值。除结果外,该方法学方法还可用于未来的研究中,以促进CTp的可重复性。

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