henhaobio
Sign in

NeuroImageMolecular BiologyPeer-reviewed journal article

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 FDG

Elizabeth A. BartlettiD, Robert Todd OgdeniD, J. John ManniD, Francesca ZanderigoiD

PDFDOIPreprint

Abstract

IntroductionFull 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 (Ki) of irreversible PET radiotracers, that requires only individual-level PET data and no blood data. We validate STARE with [18F]FDG PET and assess its performance using simulations. MethodsSTARE 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 Ki from source Ki 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 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 Ki is estimated in each region by averaging the estimates obtained in each source rotation. ResultsIn a large dataset of [18F]FDG human scans (N=69), STARE Ki estimates were in good agreement with corresponding arterial blood-based estimates (regression slope=0.88, r=0.80), and were precisely estimated, as assessed by comparing STARE Ki estimates across several runs of the algorithm (coefficient of variation across runs=6.74 {+/-} 2.48%). In simulations, STARE Ki estimates were largely robust to factors that influence the individualized anchoring used within its algorithm. ConclusionThrough simulations and application to [18F]FDG PET data, feasibility is demonstrated for STARE blood-free, data-driven quantification of Ki. Future work will include applying STARE to PET data obtained with a portable PET camera and to other irreversible radiotracers.

Citations
5
FWCI
0.57
Field percentile
top 42%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISLaurell '26Dassanayake '21Tuisku '26Tjerkaski '20Zuo '18Bhattarai '25
78% semantic matchNeuroscience