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评估大鼠脑中突触囊泡糖蛋白2A的[F]SynVesT-1正电子发射断层显像(PET)成像的非侵入性定量方法。

Assessing non-invasive quantitative methods for [F]SynVesT-1 PET imaging of synaptic vesicle glycoprotein 2A in the rat brain.

作者信息

Berckmans Lori, Schrauwen Claudia, Miranda Alan, Staelens Steven, Bertoglio Daniele

机构信息

Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, Antwerp, Belgium.

µNeuro Center for Excellence, University of Antwerp, Antwerp, Belgium.

出版信息

Eur J Nucl Med Mol Imaging. 2025 Mar 4. doi: 10.1007/s00259-025-07170-w.

Abstract

PURPOSE

Synaptic vesicle glycoprotein 2A (SV2A) is a critical biomarker for evaluating synaptic density in neurological research. Among available radioligands, [F]SynVesT-1 is increasingly used in PET research because of its extended half-life, while having comparable pharmacokinetic properties to the widely used [C]UCB-J. However, quantitative application in rat models remains unexplored for [F]SynVesT-1. This study aims to validate quantitative kinetic modelling methods for [F]SynVesT-1 and develop non-invasive quantification methods for synaptic density in rats.

METHODS

First, blood analysis of [F]SynVesT-1 was performed to generate metabolite-corrected plasma input functions. Then, kinetic modelling was evaluated using compartmental analysis approaches, as well as Logan plot. Furthermore, non-invasive image-derived input functions (IDIF), with and without non-negative matrix factorization (NMF) were compared against the arterial input function (AIF).

RESULTS

Blood analysis showed that the parent fraction of the tracer decreased over time following a sigmoid curve, while the plasma-to-whole blood ratio remained stable over time (0.89 ± 0.02). The two-tissue compartmental model (2TCM) and Logan plot were determined to be the most accurate methods for quantification of [F]SynVesT-1 kinetics in rats. Additionally, the results demonstrated strong agreement between AIF-derived and image-derived volume of distribution (V) values, with both image-derived input approaches (IDIF and IDIF-NMF) performing equally well.

CONCLUSION

These findings validate kinetic modelling methods for [F]SynVesT-1 PET, enabling their application in further rat studies for preclinical neuroscience research and prove that image-derived input functions are reliable non-invasive alternatives to AIF.

摘要

目的

突触囊泡糖蛋白2A(SV2A)是神经学研究中评估突触密度的关键生物标志物。在现有的放射性配体中,[F]SynVesT-1因其半衰期延长而越来越多地用于PET研究,同时其药代动力学特性与广泛使用的[C]UCB-J相当。然而,[F]SynVesT-1在大鼠模型中的定量应用仍未得到探索。本研究旨在验证[F]SynVesT-1的定量动力学建模方法,并开发大鼠突触密度的非侵入性定量方法。

方法

首先,对[F]SynVesT-1进行血液分析,以生成代谢物校正的血浆输入函数。然后,使用房室分析方法以及Logan图评估动力学模型。此外,将有无非负矩阵分解(NMF)的非侵入性图像衍生输入函数(IDIF)与动脉输入函数(AIF)进行比较。

结果

血液分析表明,示踪剂的母体分数随时间呈S形曲线下降,而血浆与全血的比率随时间保持稳定(0.89±0.02)。确定双组织房室模型(2TCM)和Logan图是定量大鼠[F]SynVesT-1动力学的最准确方法。此外,结果表明AIF衍生的和图像衍生的分布体积(V)值之间具有很强的一致性,两种图像衍生输入方法(IDIF和IDIF-NMF)的表现同样出色。

结论

这些发现验证了[F]SynVesT-1 PET的动力学建模方法,使其能够应用于进一步的大鼠临床前神经科学研究,并证明图像衍生输入函数是AIF可靠的非侵入性替代方法。

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