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J Nucl Med. 2009 Jun;50(6):966-73. doi: 10.2967/jnumed.108.060533. Epub 2009 May 14.
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Spillover and partial-volume correction for image-derived input functions for small-animal 18F-FDG PET studies.小动物18F-FDG PET研究中基于图像的输入函数的溢出和部分容积校正
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3
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J Nucl Med. 2007 Dec;48(12):2037-45. doi: 10.2967/jnumed.107.041061. Epub 2007 Nov 15.
4
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J Cereb Blood Flow Metab. 2008 Feb;28(2):242-50. doi: 10.1038/sj.jcbfm.9600535. Epub 2007 Aug 8.
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In vivo quantitation of glucose metabolism in mice using small-animal PET and a microfluidic device.使用小动物正电子发射断层扫描(PET)和微流控装置对小鼠体内葡萄糖代谢进行定量分析。
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一项针对小鼠全身动态氟代脱氧葡萄糖正电子发射断层扫描(FDG-PET)研究的非侵入性Patlak定量分析。

A study of non-invasive Patlak quantification for whole-body dynamic FDG-PET studies of mice.

作者信息

Zheng Xiujuan, Wen Lingfeng, Yu Shu-Jung, Huang Sung-Cheng, Feng David Dagan

机构信息

School of Medicine, Shanghai Jiaotong University, Shanghai, China.

出版信息

Biomed Signal Process Control. 2012 Sep 1;7(5):438-446. doi: 10.1016/j.bspc.2011.11.005.

DOI:10.1016/j.bspc.2011.11.005
PMID:22956982
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3433071/
Abstract

Physiological changes in dynamic PET images can be quantitatively estimated by kinetic modeling technique. The process of PET quantification usually requires an input function in the form of a plasma-time activity curve (PTAC), which is generally obtained by invasive arterial blood sampling. However, invasive arterial blood sampling poses many challenges especially for small animal studies, due to the subjects' limited blood volume and small blood vessels. A simple non-invasive quantification method based on Patlak graphical analysis (PGA) has been recently proposed to use a reference region to derive the relative influx rate for a target region without invasive blood sampling, and evaluated by using the simulation data of human brain FDG-PET studies. In this study, the non-invasive Patlak (nPGA) method was extended to whole-body dynamic small animal FDG-PET studies. The performance of nPGA was systematically investigated by using experimental mouse studies and computer simulations. The mouse studies showed high linearity of relative influx rates between the nPGA and PGA for most pairs of reference and target regions, when an appropriate underlying kinetic model was used. The simulation results demonstrated that the accuracy of the nPGA method was comparable to that of the PGA method, with a higher reliability for most pairs of reference and target regions. The results proved that the nPGA method could provide a non-invasive and indirect way for quantifying the FDG kinetics of tumor in small animal studies.

摘要

动态PET图像中的生理变化可通过动力学建模技术进行定量估计。PET定量过程通常需要以血浆-时间活性曲线(PTAC)形式的输入函数,该函数一般通过有创动脉采血获得。然而,由于实验对象血容量有限且血管细小,有创动脉采血带来了诸多挑战,尤其是在小动物研究中。最近有人提出一种基于Patlak图形分析(PGA)的简单无创定量方法,该方法利用参考区域在无需有创采血的情况下得出目标区域的相对流入率,并通过人脑FDG-PET研究的模拟数据进行了评估。在本研究中,无创Patlak(nPGA)方法被扩展应用于全身动态小动物FDG-PET研究。通过实验小鼠研究和计算机模拟系统地研究了nPGA的性能。当使用合适的基础动力学模型时,小鼠研究表明,对于大多数参考区域和目标区域对,nPGA和PGA之间的相对流入率具有高度线性。模拟结果表明,nPGA方法的准确性与PGA方法相当,对于大多数参考区域和目标区域对具有更高的可靠性。结果证明,nPGA方法可为小动物研究中肿瘤FDG动力学的定量提供一种无创且间接的方法。