Cselényi Zsolt, Olsson Hans, Halldin Christer, Gulyás Balázs, Farde Lars
Karolinska Institutet, Department of Clinical Neuroscience, Psychiatry Section, Karolinska Hospital, S-171 76 Stockholm, Sweden.
Neuroimage. 2006 Oct 1;32(4):1690-708. doi: 10.1016/j.neuroimage.2006.02.053. Epub 2006 Jul 20.
In positron emission tomography (PET) studies, the detailed mapping of neuroreceptor binding is a trade-off between parametric accuracy and spatial precision. Logan's graphical approach is a straightforward way to quickly obtain binding potential values at the voxel level but it has been shown to have a noise-dependent negative bias. More recently suggested approaches claim to improve parametric accuracy with retained spatial resolution. In the present study, we used PET measurements on regional D2 dopamine and 5-HT1A serotonin receptor binding in man to compare binding potential (BP) estimates of six different parametric imaging approaches to the traditional Logan ROI-based approach which was used as a "gold standard". The parametric imaging approaches included Logan's reference tissue graphical analysis (PILogan), its version recently modified by Varga and Szabo (PIVarga), two versions of the wavelet-based approach, Gunn's basis function method (BFM) and Gunn et al.'s recent compartmental theory-based approach employing basis pursuit strategy for kinetic modeling (called DEPICT). Applicability for practical purposes in basic and clinical research was also considered. The results indicate that the PILogan and PIVarga approaches fail to recover the correct values, the wavelet-based approaches overcome the noise susceptibility of the Logan fit with generally good recovery of BP values, and BFM and DEPICT seem to produce values with a bias dependent on receptor density. Further investigations on this bias and other phenomena revealed fundamental issues regarding the use of BFM and DEPICT on noisy voxel-wise data. In conclusion, the wavelet-based approaches seem to provide the most valid and reliable estimates across regions with a wide range of receptor densities. Furthermore, the results support the use of receptor parametric imaging in applied studies in basic or clinical research.
在正电子发射断层扫描（PET）研究中，神经受体结合的详细图谱绘制是参数准确性和空间精度之间的一种权衡。洛根的图形法是在体素水平快速获取结合潜能值的一种直接方法，但已证明它存在与噪声相关的负偏差。最近提出的方法声称能在保持空间分辨率的同时提高参数准确性。在本研究中，我们对人类大脑区域D2多巴胺和5-羟色胺1A（5-HT1A）血清素受体结合进行PET测量，以比较六种不同参数成像方法与传统基于感兴趣区域（ROI）的洛根法（用作“金标准”）对结合潜能（BP）的估计。参数成像方法包括洛根的参考组织图形分析（PILogan）、瓦尔加和萨博最近修改的版本（PIVarga）、两种基于小波的方法、冈恩的基函数法（BFM）以及冈恩等人最近基于隔室理论并采用基追踪策略进行动力学建模的方法（称为DEPICT）。还考虑了这些方法在基础和临床研究实际应用中的适用性。结果表明，PILogan和PIVarga方法无法恢复正确值，基于小波的方法克服了洛根拟合对噪声的敏感性，BP值的恢复总体良好，而BFM和DEPICT似乎产生的偏差值取决于受体密度。对这种偏差和其他现象的进一步研究揭示了在有噪声的体素数据上使用BFM和DEPICT的基本问题。总之，基于小波的方法似乎能在具有广泛受体密度的区域提供最有效和可靠的估计。此外，研究结果支持在基础或临床研究的应用中使用受体参数成像。
