Metabolic and Hemodynamic Resting-State Connectivity of the Human Brain: A High-Temporal Resolution Simultaneous BOLD-fMRI and FDG-fPET Multimodality Study

Abstract

Simultaneous [18F]-fluorodeoxyglucose positron emission tomography functional magnetic resonance imaging (FDG-PET/fMRI) provides the capacity to image 2 sources of energetic dynamics in the brain—glucose metabolism and the hemodynamic response. fMRI connectivity has been enormously useful for characterizing interactions between distributed brain networks in humans. Metabolic connectivity based on static FDG-PET has been proposed as a biomarker for neurological disease, but FDG-sPET cannot be used to estimate subject-level measures of “connectivity,” only across-subject “covariance.” Here, we applied high-temporal resolution constant infusion functional positron emission tomography (fPET) to measure subject-level metabolic connectivity simultaneously with fMRI connectivity. fPET metabolic connectivity was characterized by frontoparietal connectivity within and between hemispheres. fPET metabolic connectivity showed moderate similarity with fMRI primarily in superior cortex and frontoparietal regions. Significantly, fPET metabolic connectivity showed little similarity with FDG-sPET metabolic covariance, indicating that metabolic brain connectivity is a nonergodic process whereby individual brain connectivity cannot be inferred from group-level metabolic covariance. Our results highlight the complementary strengths of fPET and fMRI in measuring the intrinsic connectivity of the brain and open up the opportunity for novel fundamental studies of human brain connectivity as well as multimodality biomarkers of neurological diseases.

Monash DaCRA fPET-fMRI: A DAtaset for Comparison of Radiotracer Administration for high temporal resolution functional FDG-PET

“…Although very few imaging facilities world-wide currently possess the infrastructure and technical skill to acquire fPET-fMRI data, the rapid increase in publication (e.g. [5][6][7][10][11][12]14,15,21,32,33]) and reuse metrics of publicly available datasets [34,35] attests to the value the international neuroscience community places on this novel data type. The Monash DaCRA fPET-fMRI dataset is the only publicly available dataset that allows comparison of radiotracer administration protocols for fPET-fMRI.…”

Metabolic and functional connectivity provide unique and complementary insights into cognition-connectome relationships

“…Recent developments in continuous radiotracer delivery and improved PET signal detection of dual-modality magnetic resonance (MR)-PET scanners, has allowed the study of continuous glucose uptake with substantially improved temporal resolution (e.g., 60 seconds or less; Jamadar et al, 2021; Rischka et al, 2018; Villien et al, 2014). This novel method, termed “functional” FDG-PET (FDG-fPET), provides the opportunity to characterise the metabolic connectome beyond previous covariance measures resulting from static PET (Jamadar et al, 2021) and thus, approaches similar within-subject time-course correlational descriptions as exist for BOLD-fMRI hemodynamic connectivity.…”

“…Recent developments in continuous radiotracer delivery and improved PET signal detection of dual-modality magnetic resonance (MR)-PET scanners, has allowed the study of continuous glucose uptake with substantially improved temporal resolution (e.g., 60 seconds or less; Jamadar et al, 2021; Rischka et al, 2018; Villien et al, 2014). This novel method, termed “functional” FDG-PET (FDG-fPET), provides the opportunity to characterise the metabolic connectome beyond previous covariance measures resulting from static PET (Jamadar et al, 2021) and thus, approaches similar within-subject time-course correlational descriptions as exist for BOLD-fMRI hemodynamic connectivity. Using the fPET approach, we recently found that the metabolic FDG-fPET connectome showed moderate similarity with the BOLD-fMRI hemodynamic connectivity at rest, with the highest similarity between functional and metabolic connectivity obtained primarily with the superior and frontoparietal cortical areas (Jamadar et al, 2021).…”

“…This novel method, termed “functional” FDG-PET (FDG-fPET), provides the opportunity to characterise the metabolic connectome beyond previous covariance measures resulting from static PET (Jamadar et al, 2021) and thus, approaches similar within-subject time-course correlational descriptions as exist for BOLD-fMRI hemodynamic connectivity. Using the fPET approach, we recently found that the metabolic FDG-fPET connectome showed moderate similarity with the BOLD-fMRI hemodynamic connectivity at rest, with the highest similarity between functional and metabolic connectivity obtained primarily with the superior and frontoparietal cortical areas (Jamadar et al, 2021). These initial findings suggest the complementary potential of describing the human connectome via fMRI and FDG-fPET.…”

“…The present study aimed to investigate whether (1) a single global or multiple distinct connectivity pattern maps onto cognition, and whether (2) the connectome-cognition relationship is different for hemodynamic and metabolic connectivity derived from a novel FDG-fPET methodology (Jamadar et al, 2020; Jamadar et al, 2021). We acquired FDG-fPET data with high temporal resolution of 16s to measure glucose metabolic connectivity, and simultaneously acquired BOLD-fMRI data with a temporal resolution of 2.45s from 26 participants.…”