Connecting the dots: approaching a standardized nomenclature for molecular connectivity in positron emission tomography
Murray Bruce Reed, Luca Cocchi, Christin Y. Sander, Jingyuan Chen, Granville J. Matheson, Patrick M. Fisher, Tommaso Volpi, Nikkita Khattar, Christine DeLorenzo, Gregor Gryglewski, L. Silberbauer, Matej Murgaš, Godber Mathis Godbersen, Lukas Nics, Martin A. Walter, Marcus Hacker, Alessandra Bertoldo, Mark Lubberink, Mark Silfstein, R. Todd Ogden, J. John Mann, Tetsuya Suhara, Andrea Varrone, Ronald Boellaard, Roger N. Gunn, Alexander Hammers, Bharat B. Biswal, Bruce R. Rosen, Gitte M. Knudsen, Richard E. Carson, Julie Price, Rupert Lanzenberger, Andreas Hahn
Abstract
Abstract Positron emission tomography (PET)-based connectivity analysis provides a molecular perspective that complements fMRI-derived functional connectivity. However, lack of standardized terminology and diverse methodologies in PET connectivity studies has resulted in inconsistencies, complicating the interpretation and comparison of results across studies. A standardized nomenclature is thus needed to reduce ambiguity, enhance reproducibility, and facilitate interpretability across radiotracers, imaging modalities and studies. Here, we define and differentiate the terms “molecular connectivity” and “molecular covariance”. Drawing parallels from other imaging modalities, we propose “molecular connectivity” as an umbrella term to characterize statistical dependencies between the measured PET signal across brain regions at a within-subject level. Like fMRI resting-state functional connectivity, “molecular connectivity” leverages spatio-temporal associations in the PET signal to derive brain network associations. Conversely, “molecular covariance” denotes group-level computations of covariance matrices between-subjects . Further specification of the terminology can be achieved by including the target of the employed radioligand, such as “metabolic connectivity/covariance” for [ 18 F]FDG or “amyloid covariance” for [ 18 F]flutemetamol and “tau covariance” for [ 18 F]flortaucipir. While this approach to standardization aims to clarify terminology, open questions remain about the neurobiological underpinnings of these connectivity metrics. Future research should focus on elucidating these mechanisms and developing advanced computational methodologies that evaluate diverse feature relationships and improve the robustness of PET-based connectivity metrics.