[18F]Flortaucipir(FTP)PET定量通常受到来自脱靶结合(OFF)区域的溢出计数的阻碍。本工作旨在深入分析OFF在FTPPET定量中的影响,以及确定最佳的部分体积校正(PVC)策略,以最大限度地减少这个问题。
309淀粉样蛋白-β(Aβ)阴性认知正常受试者被包括在研究中。此外,使用蒙特卡罗模拟(MC)生成510个具有不同OFF级别的真实FTP图像。使用简单的两室和包括OFF区域的多区域方法对PVC的图像进行校正。FTP标准化摄取值比率(SUVR)在Braak地区(BA)进行了量化,海马体(不包括在BraakI/II中)和不同的OFF区(尾状,壳核,苍白球,丘脑,脉络丛(ChPlex),小脑白质(小脑WM),使用小脑下部作为参考区域的半球白质(半球WM)和脑脊液(CSF))。在真实和模拟PET图像中研究了OFF和皮质SUVR之间的相关性,有和没有PVC。
体内,我们发现了所有关闭区域和目标区域之间的相关性,对于半球WM尤其强(斜率>0.63,R2>0.4)。所有的相关性都减弱了,但在应用PVC后仍然显著,除了ChPlex.在MC模拟中,在所有BA中,半球WM和CSF是PVE的主要贡献者(斜率分别为0.15-0.26和0.13-0.21)。半WM(斜率=0.2),以及ChPlex(斜率=0.02),影响海马的SUVRs。小脑WM与所有目标区域呈负相关(斜率<-0.02,R2>0.8)。虽然没有发现OFF和目标区域之间的其他相关性,半球WM与所有OFF区域相关,但与小脑WM相关(斜率0.06-0.33)。应用两室PVC时,半WM相关性减弱(斜率<0.06),但是海马-ChPlex和小脑WM的相关性需要更复杂的PVC,这些区域具有专用隔室。体内,与未受PVE影响的OFF区域(16%)相比,PVC消除了在模拟研究中受PVE影响的OFF区域之间的相关性(≈50%)。
HemisWM是FTPPET溢出效应的主要驱动因素,影响目标区域和其余的OFF区域。PVC成功地降低了PVE,即使使用简单的两隔室方法。尽管PVC,体内靶区和OFF区之间仍观察到非零相关性,这表明存在生物或示踪剂相关的贡献这些相关性。
[18F]Flortaucipir (FTP) PET quantification is usually hindered by spill-in counts from off-target binding (OFF) regions. The present work aims to provide an in-depth analysis of the impact of OFF in FTP PET quantification, as well as to identify optimal partial volume correction (PVC) strategies to minimize this problem.
309 amyloid-beta (Aβ) negative cognitively normal subjects were included in the study. Additionally, 510 realistic FTP images with different levels of OFF were generated using Monte Carlo simulation (MC). Images were corrected for PVC using both a simple two-compartment and a multi-region method including OFF regions. FTP standardized uptake value ratio (
SUVR) was quantified in Braak Areas (BA), the hippocampus (which was not included in Braak I/II) and different OFF regions (caudate, putamen, pallidum, thalamus, choroid plexus (ChPlex), cerebellar white matter (cerebWM), hemispheric white matter (hemisWM) and cerebrospinal fluid (CSF)) using the lower portion of the cerebellum as a reference region. The correlations between OFF and cortical SUVRs were studied both in real and in simulated PET images, with and without PVC.
In-vivo, we found correlations between all OFF and target regions, especially strong for the hemisWM (slope>0.63, R2>0.4). All the correlations were attenuated but remained significant after applying PVC, except for the ChPlex. In MC simulations, the hemisWM and CSF were the main contributors to PVE in all BA (slopes 0.15-0.26 and 0.13-0.21 respectively). The hemisWM (slope=0.2), as well as the ChPlex (slope=0.02), influenced SUVRs in the hippocampus. The CerebWM was negatively correlated with all target regions (slope<-0.02, R2>0.8). While no other correlations between OFF and target regions were found, hemisWM was correlated with all OFF regions but the cerebWM (slopes 0.06-0.33). HemisWM correlations attenuated (slopes<0.06) when applying two-compartment PVC, but the hippocampus-ChPlex and the cerebWM correlations required more complex PVC with dedicated compartments for these regions. In-vivo, PVC removed a notably higher fraction of the correlation between OFF regions found to be affected by PVE in the simulation studies and BA (≈50%) than for OFF regions not affected by PVE (16%).
HemisWM is the main driver of spill-in effects in FTP PET, affecting both target regions and the rest of OFF regions. PVC successfully reduces PVE, even when using a simple two-compartment method. Despite PVC, non-zero correlations were still observed between target and OFF regions in vivo, which suggests the existence of biological or tracer-related contributions to these correlations.