External validation and time-stability analysis of STARE, a blood-free quantification tool for irreversible PET tracers
Year: 2026
Type: preprint
Abstract: ABSTRACT Rationale “Gold standard” blood-based quantification of dynamic 18 F-fluorodeoxyglucose ( 18 F-FDG) positron emission tomography (PET) data has limited practical clinical applications due to cost and complexity of data collection and analysis. We previously presented a blood-free quantification alternative, STARE (Source-to-Target Automatic Rotating Estimation), that was validated on 18 F-FDG data acquired on a ECAT EXACT HR+ scanner. Here, we extend that initial work by externally validating STARE using within-subject data acquired with both a Siemens Biograph mCT scanner and a portable Brain Biosciences CerePET scanner. Methods Performance was assessed by comparing regional net influx rates (K i ) estimated using STARE and the standard blood-based Patlak approach. Twenty participants underwent 60-minute 18 F-FDG scans, on two different days, once in each scanner. The time-stability of both STARE- and Patlak-based K i estimates was evaluated by applying each method to the first 20 (STARE only), 30, 40, and 50 minutes of data. Results STARE demonstrated high correlation with Patlak K i estimates across both scanner types, particularly in the Biograph mCT ( r = 0.93), with lower correlation in the CerePET ( r = 0.71). In the Biograph dataset, STARE provided reliable K i estimates at all evaluated scan durations (20 minutes and above), while in the CerePET dataset, only the 50-minute duration yielded STARE K i estimates that were not significantly different from the full 60 minutes. The Patlak approach provided K i estimates at 40 minutes scan duration and above that did not differ from the 60-min scan results in both datasets. Conclusion STARE is a viable, noninvasive alternative to traditional blood-based quantification of dynamic 18 F-FDG PET data, facilitating shorter, blood-free acquisition. This advancement could make dynamic 18 F-FDG PET imaging more accessible and comfortable for patients, promoting broader clinical adoption.
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
Award: G1849033940
OpenAlex ID: W7128639172
