Department of Biomedical Imaging & Radiological Sciences, National Yang-Ming University, No. 155, Sec. 2, Li-Nong Street, Taipei 112, Taiwan.
Neuroimage. 2012 Nov 15;63(3):1273-84. doi: 10.1016/j.neuroimage.2012.07.061. Epub 2012 Aug 6.
Positron emission tomography (PET) can be used to quantify physiological parameters. However to perform quantification requires that an input function is measured, namely a plasma time activity curve (TAC). Image-derived input functions (IDIFs) are attractive because they are noninvasive and nearly no blood loss is involved. However, the spatial resolution and the signal to noise ratio (SNR) of PET images are low, which degrades the accuracy of IDIFs. The objective of this study was to extract accurate input functions from microPET images with zero or one plasma sample using wavelet packet based sub-band decomposition independent component analysis (WP SDICA). Two approaches were used in this study. The first was the use of simulated dynamic rat images with different spatial resolutions and SNRs, and the second was the use of dynamic images of eight Sprague-Dawley rats. We also used a population-based input function and a fuzzy c-means clustering approach and compared their results with those obtained by our method using normalized root mean square errors, area under curve errors, and correlation coefficients. Our results showed that the accuracy of the one-sample WP SDICA approach was better than the other approaches using both simulated and realistic comparisons. The errors in the metabolic rate, as estimated by one-sample WP SDICA, were also the smallest using our approach.
正电子发射断层扫描（PET）可用于定量生理参数。然而，进行定量需要测量输入函数，即血浆时间活性曲线（TAC）。图像衍生的输入函数（IDIF）很有吸引力，因为它们是非侵入性的，几乎没有血液损失。然而，PET 图像的空间分辨率和信噪比（SNR）较低，这会降低 IDIF 的准确性。本研究的目的是使用基于小波包的子带分解独立成分分析（WP SDICA）从具有零或一个血浆样本的 microPET 图像中提取准确的输入函数。本研究采用了两种方法。第一种是使用具有不同空间分辨率和 SNR 的模拟动态大鼠图像，第二种是使用 8 只 Sprague-Dawley 大鼠的动态图像。我们还使用了基于群体的输入函数和模糊 c-均值聚类方法，并通过归一化均方根误差、曲线下面积误差和相关系数比较了它们与我们的方法的结果。我们的结果表明，使用模拟和真实比较，单样本 WP SDICA 方法的准确性优于其他方法。使用我们的方法，由单样本 WP SDICA 估计的代谢率误差也是最小的。
