Kinetic Modeling without Accounting for the Vascular Component Impairs the Quantification of [¹¹C]PBR28 Brain PET Data

Abstract

The positron emission tomography radioligand [ 11 C]PBR28 targets translocator protein (18 kDa) (TSPO) and is a potential marker of neuroinflammation. [ 11 C]PBR28 binding is commonly quantified using a two-tissue compartment model and an arterial input function. Previous studies with [ 11 C]-(R)-PK11195 demonstrated a slow irreversible binding component to the TSPO proteins localized in the endothelium of brain vessels, such as venous sinuses and arteries. However, the impact of this component on the quantification of [ 11 C]PBR28 data has never been investigated. In this work we propose a novel kinetic model for [ 11 C]PBR28. This model hypothesizes the existence of an additional irreversible component from the blood to the endothelium. The model was tested on a data set of 19 healthy subjects. A simulation was also performed to quantify the error generated by the standard twotissue compartmental model when the presence of the irreversible component is not taken into account. Our results show that when the vascular component is included in the model the estimates that include the vascular component (2TCM-1K) are more than three-fold smaller, have a higher time stability and are better correlated to brain mRNA TSPO expression than those that do not include the model (2TCM).

Pharmacokinetic Analysis of 11C-PBR28 in the Rat Model of Herpes Encephalitis: Comparison with (R)-11C-PK11195

“…This might be explained by the presence of TSPO receptors in red blood cells, which can bind the tracer. This binding seems to be more important for the second-generation TSPO tracers with higher affinity for TSPO (e.g., 11 C-PBR28) than for (R)-11 C-PK11195 (25). The 2TCM is considered the most suitable model for pharmacokinetic analysis of the receptor ligands 11 C-PBR28 (26) and (R)-11 C-PK11195 (27).…”

Flutriciclamide (18F-GE180) PET: First-in-Human PET Study of Novel Third-Generation In Vivo Marker of Human Translocator Protein

“…18 F-GE180 tissue data were investigated with the reversible 1-tissue 2k (1TCM2k) model, the 2-tissue 4k (2TCM4k) model, and the irreversible 2-tissue 3k, for which k implies the rate constant for tracer for different kinetic compartments. As tracer binds to BBB endothelial cells, endothelia could significantly affect kinetic modeling (7,13); therefore, we also considered 1 tissue with extra vascular component (1TCM2k-1k) and 2-tissue with extra vascular component (2TCM4k-1k). The additional component describes the trapping of the tracer by the endothelial cells of blood vessels.…”

“…The first factor is genetic: a single nucleotide polymorphism in the TSPO gene (rs6971) leads to an amino-acid substitution (A147T) and reduced binding affinity. The second factor is the disproportion between the high signal from the TSPO in the endothelial cells of the blood-brain barrier (BBB) and venous sinuses and the signal from the tissue, requiring appropriate kinetic correction (7). The third factor is the difficulty in obtaining accurate estimates of free plasma concentrations for proper quantification.…”

The precise physiological definition of tissue perfusion and clearance measured from imaging

“…The values of the transport constants that between them generate the curve that most closely resembles the measured tissue curve are computed using the least squares approach. The blood volume of the organ, as a proportion of total organ volume (vascular fraction, V b ), is generally included as a model parameter in the computation [7]. The interstitial space, however, increases modelling complexity so is usually ignored.…”

“…The extent to which this matters depends on the magnitude of the vascular fraction. Tissue blood volume as a proportion of total volume varies from 0.05 for the brain [7], to~0.1 for the myocardium [17] and to~0.25 for the liver [12]. For the liver, however, the vascular fraction includes a large interstitial space, termed 'extended blood volume' by Munk et al [12], who found a mean value of 0.4 in pigs.…”