Abstract
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Objectives 6 ADs (age=58.8±6.9), 9 HCs (age=79.1±7.2) and 3 yHCs (age=21.7±0.6) were scanned on a Siemens Biograph TruePoint 6 PET/CT using AV-1451.
Methods Subjects were scanned 0-150 min post-injection with a break from 100-120 min, framed as 4x15 sec, 8x30 sec, 9x60 sec, 2x180 sec, 22x300 sec. Data were realigned across frames and coregistered to a T1-weighted MRI. The MRI was segmented using Freesurfer to obtain 113 standard regions of interest (ROIs). PET scans were analyzed using CIFA1 and SRTM2,3(cerebellar gray=reference region). 4 factors were identified in CIFA1 as arterial, venous, specific (slower time course) and non-specific (faster time course) binding. Correlations between BPND and specific and non-specific binding factors were calculated. Patterns between non-specific binding and MAO-A measurement4 were explored.
Results Figure 1a shows a representative time series for the 4 factors. Factor 1 and 2 were interpreted as relating to arterial and venous blood, factor 3 represents non-specific binding, factor 4 represents the specific binding. Specific and non-specific binding factors are differentiated because the clearance rate for regions with tau accumulation is slower than regions that should not have tau. Figure 1b shows the corresponding time activity curves for cerebellar gray, thalamus (non-specific binding region), and temporal cortex (specific binding region). Figure 2a shows BPND versus specific and non-specific binding factor for an AD subject across 113 ROIs. Figure 2b plots the r2 for correlations across all subjects. AD specific binding showed high correlations with BPND. The 2 HCs with the highest r2 between BPND and specific binding also had elevated BPND in temporal and parietal cortices in comparison to the other HCs. We looked at the ratio of non-specific to specific binding in cerebellar gray (ADs=4.9±1.7, HCs=4.6±2.9, yHCs=1.5±0.4), showing that the reference region is dominated by non-specific binding in HCs and ADs. The ratio of non-specific to specific in temporal cortex was AD=0.7±0.3, HCs=1.7±0.8; in thalamus it was ADs=4.0±1.8, and HCs=2.1±1.4. Lastly, we compare MAO-A measurements4 to non-specific binding values shown in Figure 3.
Conclusions CIFA specific binding correlates well with BPND in ADs, but not in HCs and yHCs, probably reflecting the difficulty of parsing out specific and non-specific binding signal in SRTM. Cerebellar gray signal is dominated by non-specific binding, making it a good choice for reference region. 1. Boutchko R, Mitra D, Baker SL, et al. Clustering-Initiated Factor Analysis Application for Tissue Classification in Dynamic Brain PET. J Cereb Blood Flow Metab. 2015; 35(7):1104-1111. 2. Lammertsma A, Hume SP (1996). Simplified Reference Tissue Model for PET Receptor Studies. Neuroimage. 1996;4: 153-158. 3. Gunn RN, Lammertsma AA, Hume SP, Cunningham VJ. Parametric imaging of ligand-receptor binding in PET using a simplified reference region model. Neuroimage. 1997;6(4): 279-287. 4. Fowler HS, Alia-Klein N, Kriplani A, et al. Evidence That Brain MAO A Activity Does Not Correspond To MAO A Gentotype in Healthy Male Subjects. Biological Psychiatry. 2007; 62(4):355-358.