Suppr超能文献

动态PET研究的光谱分析:20年方法发展与应用综述

Spectral Analysis of Dynamic PET Studies: A Review of 20 Years of Method Developments and Applications.

作者信息

Veronese Mattia, Rizzo Gaia, Bertoldo Alessandra, Turkheimer Federico E

机构信息

Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Department of Information Engineering, University of Padova, Padova, Italy.

出版信息

Comput Math Methods Med. 2016;2016:7187541. doi: 10.1155/2016/7187541. Epub 2016 Dec 5.

Abstract

In Positron Emission Tomography (PET), spectral analysis (SA) allows the quantification of dynamic data by relating the radioactivity measured by the scanner in time to the underlying physiological processes of the system under investigation. Among the different approaches for the quantification of PET data, SA is based on the linear solution of the Laplace transform inversion whereas the measured arterial and tissue time-activity curves of a radiotracer are used to calculate the input response function of the tissue. In the recent years SA has been used with a large number of PET tracers in brain and nonbrain applications, demonstrating that it is a very flexible and robust method for PET data analysis. Differently from the most common PET quantification approaches that adopt standard nonlinear estimation of compartmental models or some linear simplifications, SA can be applied without defining any specific model configuration and has demonstrated very good sensitivity to the underlying kinetics. This characteristic makes it useful as an investigative tool especially for the analysis of novel PET tracers. The purpose of this work is to offer an overview of SA, to discuss advantages and limitations of the methodology, and to inform about its applications in the PET field.

摘要

在正电子发射断层扫描(PET)中,光谱分析(SA)通过将扫描仪在不同时间测量的放射性与所研究系统的潜在生理过程相关联,实现对动态数据的量化。在PET数据量化的不同方法中,SA基于拉普拉斯变换反演的线性解,利用放射性示踪剂的测量动脉和组织时间-活度曲线来计算组织的输入响应函数。近年来,SA已在大量脑和非脑应用的PET示踪剂中得到应用,表明它是一种非常灵活且稳健的PET数据分析方法。与采用隔室模型的标准非线性估计或一些线性简化的最常见PET量化方法不同,SA无需定义任何特定模型配置即可应用,并且已证明对潜在动力学具有非常好的敏感性。这一特性使其成为一种有用的研究工具,尤其适用于新型PET示踪剂的分析。本文的目的是对SA进行概述,讨论该方法的优缺点,并介绍其在PET领域的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1776/5165231/f09a270a3dff/CMMM2016-7187541.001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验