Source-to-Target Automatic Rotating Estimation (STARE) – A publicly-available, blood-free quantification approach for PET tracers with irreversible kinetics: Theoretical framework and validation for [(18)F]FDG

INTRODUCTION: Full quantification of positron emission tomography (PET) data requires an input function. This generally means arterial blood sampling, which is invasive, labor-intensive and burdensome. There is no current, standardized method to fully quantify PET radiotracers with irreversible kinetics in the absence of blood data. Here, we present Source-to-Target Automatic Rotating Estimation (STARE), a novel, data-driven approach to quantify the net influx rate (K(i)) of irreversible PET radiotracers, that requires only individual-level PET data and no blood data. We validate STARE with human [(18)F]FDG PET scans and assess its performance using simulations. METHODS: STARE builds upon a source-to-target tissue model, where the tracer time activity curves (TACs) in multiple “target” regions are expressed at once as a function of a “source” region, based on the two-tissue irreversible compartment model, and separates target region K(i) from source K(i) by fitting the source-to-target model across all target regions simultaneously. To ensure identifiability, data-driven, subject-specific anchoring is used in the STARE minimization, which takes advantage of the PET signal in a vasculature cluster in the field of view (FOV) that is automatically extracted and partial volume-corrected. To avoid the need for any a priori determination of a single source region, each of the considered regions acts in turn as the source, and a final K(i) is estimated in each region by averaging the estimates obtained in each source rotation. RESULTS: In a large dataset of human [(18)F]FDG scans (N = 69), STARE K(i) estimates were correlated with corresponding arterial blood-based K(i) estimates (r = 0.80), with an overall regression slope of 0.88, and were precisely estimated, as assessed by comparing STARE K(i) estimates across several runs of the algorithm (coefficient of variation across runs=6.74 ± 2.48%). In simulations, STARE K(i) estimates were largely robust to factors that influence the individualized anchoring used within its algorithm. CONCLUSION: Through simulations and application to [(18)F]FDG PET data, feasibility is demonstrated for STARE blood-free, data-driven quantification of K(i). Future work will include applying STARE to PET data obtained with a portable PET camera and to other irreversible radiotracers.