A generalized framework for <i>in vivo</i> detection of dopamine release using positron emission tomography.

ABSTRACT: Voxel-level detection of task-induced striatal dopamine (DA) release in humans is achievable with dynamic PET imaging, enabling complex studies of motor, cognitive, and reward tasks. We previously introduced a data-driven methodology termed Residual Space Detection (RSD), which improved detection of low-amplitude DA release, however its applicability was limited to detection of low-amplitude and/or localized effects. Here, we generalize RSD to broader DA release scenarios by introducing a novel model-based baseline time-activity curve prediction method in combination with non-local-means clustering (RSD-Hybrid-IMRTM). In simulations, RSD-Hybrid-IMRTM outperforms our previous methodology for detecting global striatal DA release, improving absolute detection sensitivity by 18% at 5% false po

SUBMITTER: Hanania JU 

PROVIDER: S-EPMC12449306 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature