A novel blood-free analytical framework for the quantification of neuroinflammatory load from TSPO PET imaging

Positron Emission Tomography (PET) of 18 kDa translocator protein (TSPO) has been investigated as putative marker of neuroinflammation but faces substantial methodological challenges. These include issues with arterial blood sampling for kinetic modeling, the absence of suitable reference regions, genetic polymorphisms affecting tracer affinity, altered blood-to-brain tracer delivery in inflammatory conditions, and high signal variability. This study presents a novel blood-free reference-free method for TSPO PET quantification, leveraging a logistic regression model to estimate the probability of TSPO overexpression across brain regions. Validation was performed on 323 human brain scans from five datasets and three radiotracers. The quantified TSPO topology in healthy controls showed strong concordance with constitutive TSPO gene expression for all tracers. When using [¹¹C]PBR28 PET data, the method replicated previous findings in schizophrenia, Alzheimer's disease, chronic pain, and XBD173 blocking. However, model extension to [¹⁸F]DPA-714 and [¹¹C]-(R)-PK11195 revealed small effect sizes and high variability, suggesting the need for tracer-specific model optimization. Finally, validation in a rat model of lipopolysaccharide-induced neuroinflammation confirmed previous evidence of increased brain TSPO uptake after systemic challenge. This novel non-invasive method provides individualized TSPO PET quantification, demonstrating broad applicability across TSPO PET tracers and imaging sites, assuming sufficient training data for model development.