Suppr超能文献

校正血浆葡萄糖水平升高对使用FDG-PET进行MR(glc)定量的影响。

Correction for the effect of rising plasma glucose levels on quantification of MR(glc) with FDG-PET.

作者信息

Dunn Joel T, Anthony Karen, Amiel Stephanie A, Marsden Paul K

机构信息

Division of Imaging Sciences, PET Imaging Centre, King's College London, St Thomas' Hospital, London, UK.

出版信息

J Cereb Blood Flow Metab. 2009 May;29(5):1059-67. doi: 10.1038/jcbfm.2009.21. Epub 2009 Mar 18.

Abstract

Positron emission tomography (PET) using the tracer [18F]-fluorodeoxyglucose (FDG) is commonly used for measuring metabolic rate of glucose (MR(glc)) in the human brain. Conventional PET methods (e.g., the Patlak method) for quantifying MR(glc) assume the tissue transport and phosphorylation mechanisms to be in steady state during FDG uptake. As FDG and glucose use the same transporters and phosphorylation enzymes, changing blood glucose levels can change the rates of FDG transport and phosphorylation. Compartmental models were used to simulate the effect of rising arterial glucose, from normal to hyperglycemic levels on FDG uptake for a typical PET protocol. The subsequent errors on the values of MR(glc) calculated using the Patlak method were investigated, and a correction scheme based on measured arterial glucose concentration (G(p)) was evaluated. Typically, with a 40% rise in G(p) over the duration of the PET study, the true MR(glc) varied by only 1%; however, the Patlak method overestimated MR(glc) by 15%. The application of the correction reduced this error to approximately 2%. In general, the application of the correction resulted in values of MR(glc) consistently significantly closer to the true steady state calculation of MR(glc) independently of changes to the parameters defining the model.

摘要

使用示踪剂[18F]-氟脱氧葡萄糖(FDG)的正电子发射断层扫描(PET)通常用于测量人脑的葡萄糖代谢率(MR(glc))。用于量化MR(glc)的传统PET方法(例如Patlak方法)假定在FDG摄取期间组织转运和磷酸化机制处于稳态。由于FDG和葡萄糖使用相同的转运体和磷酸化酶,血糖水平的变化会改变FDG的转运和磷酸化速率。使用房室模型来模拟动脉葡萄糖从正常水平升高到高血糖水平对典型PET方案中FDG摄取的影响。研究了使用Patlak方法计算的MR(glc)值的后续误差,并评估了基于测量的动脉葡萄糖浓度(G(p))的校正方案。通常,在PET研究期间G(p)升高40%时,真实的MR(glc)仅变化1%;然而,Patlak方法高估了MR(glc) 15%。校正的应用将此误差降低到约2%。一般来说,校正的应用使得MR(glc)值始终显著更接近MR(glc)的真实稳态计算值,而与定义模型的参数变化无关。

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