Biomarkers.

Area of Science:

• Neuroimaging
• Radiochemistry
• Nuclear Medicine

Background:

• [18F]MK6240 PET imaging shows high affinity for Alzheimer's disease (AD) tauopathy.
• Meningeal and extracerebral off-target signals complicate early tau detection.
• Previous work demonstrated irreversible kinetics of off-target signals.

Purpose of the Study:

• To evaluate an alternative compartmental model (2TCM+s) for quantifying extracerebral contamination.
• To compare the performance of the 2TCM+s model against partial volume correction (PVC) for early tau detection.
• To assess the impact of the 2TCM+s model on late-frame Standardized Uptake Value Ratio (SUVR).

Main Methods:

• Thirteen participants (8 controls, 5 MCI) underwent 2-hr [18F]MK6240 PET, MRI, and arterial sampling.
• A within-reconstruction kernel-based PVC was applied to a subset of participants.
• Regional uptake was modeled using standard 2-tissue compartmental model (2TCM), 2TCM+s, and 2TCM-kernel.

Main Results:

• The 2TCM+s model showed the best performance based on Akaike Information Criteria (AIC).
• The extracerebral term 's' quantified contamination, highest in regions near the meninges.
• SUVR with 2TCM+s correction exhibited the largest effect size for differentiating controls from MCI patients.

Conclusions:

• Compartmental modeling (2TCM+s) quantifies [18F]MK6240 extracerebral contamination, improving accuracy and sensitivity for early tau detection.
• This approach shows potential advantages over PVC.
• Future studies will validate these corrections in larger cohorts and non-dynamic PET data.