Graphic plot analysis for estimating binding potential of translocator protein (TSPO) in positron emission tomography studies with [¹⁸F]FEDAA1106

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• 作者：Yoko Ikoma ; Akihiro Takano ; ^{Akihiro.Takano@ki.se} ; Andrea Varrone ; Christer Halldin
• 关键词：Positron emission tomography ; Translocator protein (TSPO) ; Binding potential ; Graphical analysis
• 刊名：NeuroImage
• 出版年：2013
• 出版时间：1 April, 2013
• 年：2013
• 卷：69
• 期：Complete
• 页码：78-86
• 全文大小：963 K

文摘

Purpose

[¹⁸F]FEDAA1106 is expected to be used for evaluating the regional density of the peripheral benzodiazepine receptor (also called TSPO) in several neurodegenerative disorders. Regarding the quantification, direct binding potential (BP_ND) has been reported to be preferable because of the variation of nondisplaceable distribution volume (V_ND) among individuals. However, the precise calculation of BP_ND is difficult in small regions or at voxel levels due to noise. Recently, a new graphical analysis (GA) was proposed to estimate V_ND in a direct way. In this paper, we evaluated two types of GA for reliable quantification of BP_ND in PET study with [¹⁸F]FEDAA1106 using computer simulations and human data.

Methods

In the simulations, time-activity curves were generated with various rate constants and noise levels, and the errors of BP_ND estimated by GA were analyzed by comparing with true values calculated from rate constants given for the simulations. Thereafter, in a human study with [¹⁸F]FEDAA1106 for healthy volunteers, BP_ND was estimated by two types of GA for region-of-interest (ROI) data. Parametric images of BP_ND were generated by two types of GA with or without wavelet-denoising.

Results

Simulations showed that BP_ND by GA was well correlated with true values, despite an underestimation. GA reduced unreasonable estimates compared with a conventional nonlinear least-square fitting (NLS), although larger variation of BP_ND estimates was observed. In a ROI-based analysis of data obtained in a human study, BP_NDs estimated by GA were well correlated with those generated by NLS, though they were underestimated. Parametric BP_ND images by GA could be improved with wavelet-denoising.

Conclusion

Graphical analysis could provide BP_ND values with high stability and simple calculation in both ROI-based and voxel-based analyses of [¹⁸F]FEDAA1106 data.