P083] Kinetic modelling of [68Ga]Ga-DOTA-Siglec-9 in a porcine infection model

Abstract

Purpose Localized infections deep in the body can be hard to diagnose. Positron emission tomography (PET) can scan inside the body, but depends on the availability of suitable tracers. The PET tracer [ 68 Ga]Ga-DOTA-Siglec-9 binds to a protein involved in leukocyte extravasation (vascular adhesion protein 1, VAP-1). Uptake of the tracer in infection has been demonstrated in several studies. Kinetic modelling can give insight into the mechanism of uptake and release, but so far kinetic modelling of the tracer has only been attempted for lung inflammation. The present study investigates the kinetics of [ 68 Ga]Ga-DOTA-Siglec-9 in a porcine infection model, comprising both bone infections (osteomyelitis) and soft tissue infections. Methods Eight female juvenile (19–25 kg) domestic pigs were inoculated with Staphylococcus aureus in the right femoral artery in order to selectively induce infection in the right hind limb. Pigs with sign of osteomyelitis after one week were dynamically PET/CT-scanned with [ 68 Ga]Ga-DOTA-Siglec-9 and blood sampling. The animals were then euthanised and necropsied. Volumes of interest (VOIs) were drawn on PET/CT images around identified infections, paired with VOIs in the same anatomical position in the left hind limb as control. PET data from the VOIs were kinetically modelled with three compartment models: a one-tissue compartment model (1TCM), a two-tissue model with irreversible uptake (irr2TCM), and a two-tissue model with reversible uptake (rev2TCM). Patlak and Logan plots were also investigated. Results In the eight pigs, VOIs were drawn around 10 bone infections and 12 soft tissue infections. Generally, Logan plots were linear while many Patlak plots were not, indicating a reversible uptake process. In line with this result, most data sets required the rev2TCM model for successful fitting. Compared to the VOIs in the control limb, distribution volume (DV) for [68Ga]Ga-DOTA-Siglec-9 was found to be significantly elevated in the soft tissue infections, but not in the bone infections. Conclusions Uptake of [68Ga]Ga-DOTA-Siglec-9 had reversible kinetics, which could be modelled with the rev2TCM (4 k-parameters). Distribution volume for the uptake was only elevated in soft tissue infections. This points to the tracer having a role in infections involving soft tissue, but not for bone infections (osteomyelitis).