A new framework for metabolic connectivity mapping using bolus [¹⁸F]FDG PET and kinetic modeling.

ABSTRACT: Metabolic connectivity (MC) has been previously proposed as the covariation of static [¹⁸F]FDG PET images across participants, i.e., across-individual MC (ai-MC). In few cases, MC has been inferred from dynamic [¹⁸F]FDG signals, i.e., within-individual MC (wi-MC), as for resting-state fMRI functional connectivity (FC). The validity and interpretability of both approaches is an important open issue. Here we reassess this topic, aiming to 1) develop a novel wi-MC methodology; 2) compare ai-MC maps from standardized uptake value ratio (SUVR) vs. [¹⁸F]FDG kinetic parameters fully describing the tracer behavior (i.e., K_i, K₁, k₃); 3) assess MC interpretability in comparison to structural

SUBMITTER: Volpi T 

PROVIDER: S-EPMC10676136 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature