Wavelet analysis of dynamic PET data:: Application to the parametric imaging of benzodiazepine receptor concentration
Wavelet analysis of dynamic PET data:: Application to the parametric imaging of benzodiazepine receptor concentration
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DOI：
10.1006/nimg.2000.0563
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发表时间：
2000-05-01
期刊：
影响因子：
5.7
通讯作者：
Guimón, J
中科院分区：
文献类型：
--
作者：
Millet, P;Ibáñez, V;Guimón, J
受体密度和配体亲和力可以用正电子发射断层扫描(PET)来评估。生物参数(B-max‘，k(1)，k(2)，k(On)/V-R，k(Off))采用隔室模型和多次注射方案进行估算。配基-受体模型的参数成像已被证明对研究某些大脑疾病特别感兴趣。然而，像素级动力学曲线的低信噪比阻碍了在优化过程中对模型参数的充分估计。因此，映射需要空间过滤器，从而导致分辨率损失。用傅里叶变换对动力学曲线进行频域滤波是不合适的，因为难以选择正确有效的截止频率，基于小波的滤波器更适合于这种示踪动力学。本研究的目的是利用小波滤波，在保持原有空间分辨率的前提下，在像素级建立参数图像。数据来自[C-11]氟马西尼研究，绘制了苯二氮卓类受体密度图。利用可逆离散小波变换逐像素计算时间-浓度PET曲线的时频信号。利用在高、低受体密度区观察到的大范围感兴趣区域的动力学曲线来校准小波系数的阈值。然后将压缩后的小波系数变换回原始域，得到滤波后的PET信号。在像素水平上获得了所有结合参数的图，在大多数灰质中，B-max‘参数的可接受变异系数小于30%，对于所有模型参数，使用通常感兴趣区域的模型参数估计与参数成像之间存在很强的相关性(B-max’参数的r=0.949)。我们的结论是，基于小波的过滤器在不损失PET扫描仪的原始空间分辨率的情况下，对于建立绑定参数图是有用的。基于小波的滤波方法的使用可以远远扩展到多注射协议之外，它很可能也适用于其他动态PET研究。(C)2000年学术出版社。
Receptor density and ligand affinity can be assessed using positron emission tomography (PET). Biological parameters (B-max', k(1), k(2), k(on)/V-R, k(off)) are estimated using a compartmental model and a multi-injection protocol. Parametric imaging of the ligand-receptor model has been shown to be of special interest to study certain brain disorders. However, the low signal-to-noise ratio in kinetic curves at the pixel level hampers an adequate estimation of model parameters during the optimization procedure. For this reason, mapping requires a spatial filter, resulting in a loss of resolution. Filtering the kinetic curves in the frequency domain using the Fourier transform is not appropriate, because of difficulties in choosing a correct and efficient cutoff frequency, A wavelet-based filter is more appropriate to such tracer kinetics. The purpose of this study is to build up parametric images at the pixel level while conserving the original spatial resolution, using wavelet-based filtering. Data from [C-11]flumazenil studies, mapping the benzodiazepine receptor density, were used. An invertible discrete wavelet transform was used to calculate the time-frequency signals of the time-concentration PET curves on a pixel-by-pixel basis. Kinetic curves observed from large regions of interest in high and low receptor-density regions were used to calibrate the threshold of wavelet coefficients. The shrunken wavelet coefficients were then transformed back to the original domain in order to obtain the filtered PET signal. Maps of all binding parameters were obtained at the pixel level with acceptable coefficients of variation of less than 30% for the B-max' parameter in most of the gray matter, A strong correlation between model parameter estimates using the usual regions of interest and parametric imaging was observed for all model parameters (r = 0.949 for the parameter B-max'). We conclude that wavelet-based filters are useful for building binding parameter maps without loss of the original spatial resolution of the PET scanner. The use of the wavelet-based filtering method can be extended far beyond the multi injection protocol, It is likely to be also effective for other dynamic PET studies. (C) 2000 Academic Press.