From metabolic connectivity to molecular connectivity: application to dopaminergic pathways

Abstract

This study aims to reveal the feasibility and potential of molecular connectivity based on neurotransmission in comparison to the metabolic connectivity with an application to dopaminergic pathways. For this purpose, we propose to compare the neurotransmission connectivity findings using 123 I-FP-CIT SPECT and 18 F-FDOPA PET to the metabolic connectivity findings using 18 F-FDG PET. Methods: 18 F-FDG PET and 123 I-FP-CIT SPECT images from 47 subjects and 18 F-FDOPA PET images from 177 subjects, who had no neurological or psychiatric disorders, were studied. Interregional correlation analyses were performed at the group level to determine the midbrain's connectivity via glucose metabolic rate using 18 F-FDG PET, and via dopaminergic binding potential using 123 I-FP-CIT SPECT and 18 F-FDOPA PET. SPM-T maps of each radiotracer were generated, and masks used to highlight the significant differences obtained among the imaging modalities and targets. Results: The three dopaminergic pathways (i.e. nigrostriatal, mesolimbic and mesocortical) were identified by 18 F-FDG PET (1,599 voxels, with a T-max value of 12.6), 123 I-FP-CIT SPECT (1,120 voxels, with T-max value of 5.1), and 18 F-FDOPA PET (6,054 voxels, with Tmax value of 11.7) for a T-voxel threshold of 5.10, 2.80 and 5.10, respectively. Using the same T-voxel threshold of 5.10, 18 F-FDOPA PET showed more specific findings than 18 F-FDG PET with less voxels identified outside these pathways (-9,323 voxels), whereas no significant voxels were obtained with 123 I-FP-CIT SPECT at this threshold. Conclusion: The present study illustrates the feasibility and interest in using molecular connectivity with 18 F-FDOPA PET for dopaminergic pathways. Such analyses could be applied to specific diseases involving the dopaminergic system.

Dopamine D1-Receptor Organization Contributes to Functional Brain Architecture

“…IRCA produces robust network metrics with high test-retest reliability (Veronese et al, 2019), even with relatively modest sample sizes (Horwitz et al, 1984;Caminiti et al, 2017a). PET IRCA has previously been used to investigate metabolic connectivity (Horwitz et al, 1987(Horwitz et al, , 1988(Horwitz et al, , 1991Lee et al, 2008;Di and Biswal, 2012;Morbelli et al, 2012;Sala et al, 2017;Caminiti et al, 2017b) and organization of catecholamine receptors (Cervenka et al, 2010;Zald et al, 2010;Rieckmann et al, 2011b;Tuominen et al, 2014;de Boer et al, 2019;Papenberg et al, 2019), transporters (Vanicek et al, 2017), and synthesis capacity (Cselényi et al, 2004;Verger et al, 2020). However, the method of cross-correlating ligand binding across subjects may be sensitive to interindividual differences (Veronese et al, 2019).…”

Single Photon Emission Computed Tomography/Positron Emission Tomography Molecular Imaging for Parkinsonism: A Fast‐Developing Field

“…The 18 F‐FDG radiotracer is also more commonly used and static imaging acquisitions are more easily applicable than dynamic ones. 53 These analytical approaches have now also been applied to dopaminergic imaging 54 and have been further validated in patients with movement disorders. 55 , 56 Molecular connectivity modeling approaches may improve our understanding of neurodegenerative movement disorder pathogeneses and provide a comprehensive strategy to identify the pathological networks involved.…”

Similarity between structural and proxy estimates of brain connectivity

“… 19 Similar to sMRI, PET-based connectivity estimation is commonly performed at a group level. This approach has been successfully applied to PET measures of glucose metabolism, 20 – 22 neurotransmission, 23 , 24 and pathological protein aggregations. 25 – 27 The most popular approach has been PET with 18 F-Fluordesoxyglucose (FDG), sometimes referred to in the literature as metabolic connectivity.…”