Seo Seongho, Kim Su Jin, Lee Dong Soo, Lee Jae Sung
Department of Nuclear Medicine, College of Medicine, Seoul, Korea.
Neurosci Bull. 2014 Oct;30(5):733-54. doi: 10.1007/s12264-014-1465-9. Epub 2014 Sep 28.
Tracer kinetic modeling in dynamic positron emission tomography (PET) has been widely used to investigate the characteristic distribution patterns or dysfunctions of neuroreceptors in brain diseases. Its practical goal has progressed from regional data quantification to parametric mapping that produces images of kinetic-model parameters by fully exploiting the spatiotemporal information in dynamic PET data. Graphical analysis (GA) is a major parametric mapping technique that is independent on any compartmental model configuration, robust to noise, and computationally efficient. In this paper, we provide an overview of recent advances in the parametric mapping of neuroreceptor binding based on GA methods. The associated basic concepts in tracer kinetic modeling are presented, including commonly-used compartment models and major parameters of interest. Technical details of GA approaches for reversible and irreversible radioligands are described, considering both plasma input and reference tissue input models. Their statistical properties are discussed in view of parametric imaging.
动态正电子发射断层扫描(PET)中的示踪剂动力学建模已被广泛用于研究脑部疾病中神经受体的特征分布模式或功能障碍。其实际目标已从区域数据量化发展到参数映射,即通过充分利用动态PET数据中的时空信息来生成动力学模型参数图像。图形分析(GA)是一种主要的参数映射技术,它独立于任何房室模型配置,对噪声具有鲁棒性,并且计算效率高。在本文中,我们概述了基于GA方法的神经受体结合参数映射的最新进展。介绍了示踪剂动力学建模中的相关基本概念,包括常用的房室模型和主要感兴趣的参数。考虑血浆输入和参考组织输入模型,描述了可逆和不可逆放射性配体的GA方法的技术细节。从参数成像的角度讨论了它们的统计特性。