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首页> 外文期刊>The Journal of Nuclear Medicine >Blind separation of cardiac components and extraction of input function from H(2)(15)O dynamic myocardial PET using independent component analysis.
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Blind separation of cardiac components and extraction of input function from H(2)(15)O dynamic myocardial PET using independent component analysis.

机译:盲分离心脏成分并使用独立成分分析从H(2)(15)O动态心肌PET中提取输入功能。

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The independent component analysis (ICA) method is suggested to be useful for separation of the ventricles and the myocardium and for extraction of the left ventricular input function from the dynamic H(2)(15)O myocardial PET. The ICA-generated input function was validated with the sampling method, and the myocardial blood flow (MBF) calculated with this input function was compared with the microsphere results. METHODS: We assumed that the elementary activities of the ventricular pools and the myocardium were spatially independent and that the mixture of them composed dynamic PET image frames. The independent components were estimated by recursively minimizing the mutual information (measure of dependence) between the components. The ICA-generated input functions were compared with invasively derived arterial blood samples. Moreover, the regional MBF calculated using the ICA-generated input functions and single-compartment model was correlated with the results obtained from the radiolabeled microspheres. RESULTS: The ventricles and the myocardium were successfully separated in all cases within a short computation time (<15 s). The ICA-generated input functions displayed shapes similar to those obtained by arterial sampling except that they had a smoother tail than those obtained by sampling, which meant that ICA removed the statistical noise from the time--activity curves. The ICA-generated input function showed a longer time delay of peaks than those obtained by arterial sampling. MBFs estimated using the ICA-generated input functions ranged from 1.10 to approximately 2.52 mL/min/g at rest and from 1.69 to approximately 8.00 mL/min/g after stress and correlated well with those calculated with microspheres (y = 0.45 + 0.98x; r = 0.95, P < 0.000). CONCLUSION: ICA, a rapid and reliable method for extraction of the pure physiologic components, was a valid and useful method for quantification of the regional MBF using H(2)(15)O PET.
机译:建议使用独立成分分析(ICA)方法来分离心室和心肌,以及从动态H(2)(15)O心肌PET提取左心室输入功能。用采样方法验证了ICA生成的输入函数,并将使用该输入函数计算的心肌血流量(MBF)与微球结果进行了比较。方法:我们假设心室池和心肌的基本活动在空间上是独立的,并且它们的混合物组成了动态PET图像帧。通过递归最小化组件之间的相互信息(依赖性度量)来估计独立组件。将ICA生成的输入功能与侵入性动脉血样本进行比较。此外,使用ICA生成的输入函数和单室模型计算的区域MBF与从放射性标记微球获得的结果相关。结果:在所有情况下,心室和心肌均在短时间内(<15 s)成功分离。 ICA生成的输入函数显示的形状类似于通过动脉采样获得的输入函数,只是它们的尾部比通过采样获得的平滑,这意味着ICA从时间-活动曲线中消除了统计噪声。 ICA生成的输入函数显示出比通过动脉采样获得的峰更长的峰时间延迟。使用ICA生成的输入函数估算的MBF在静止状态下的范围从1.10到约2.52 mL / min / g,在压力后的范围从1.69到约8.00 mL / min / g,与微球计算的MBF很好地相关(y = 0.45 + 0.98x ; r = 0.95,P <0.000)。结论ICA是一种快速可靠的纯生理成分提取方法,是一种使用H(2)(15)O PET定量MBF的有效方法。

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