Integrity of neurocognitive networks in dementing disorders as measured with simultaneous pet/functional mri - Ripp, Isabelle; Stadhouders, Thomas; Savio, Alexandre; Goldhardt, Oliver; Cabello, Jorge; Calhoun, Vince; Riedl, Valentin; Hedderich, Dennis; Diehl-Schmid, Janine; Grimmer, Timo; Yakushev, Igor (Journal of Nuclear Medicine, 2020)
Functional MRI (fMRI) studies have reported altered integrity of large-scale neurocognitive networks (NCNs) in dementing disorders. However, findings on the specificity of these alterations in patients with Alzheimer disease (AD) and behavioral-variant frontotemporal dementia (bvFTD) are still limited. Recently, NCNs have been successfully captured using PET with 18F-FDG. Methods: Network integrity was measured in 72 individuals (38 male) with mild AD or bvFTD, and in healthy controls, using a simultaneous restingstate fMRI and 18F-FDG PET. Indices of network integrity were calculated for each subject, network, and imaging modality. Results: In either modality, independent-component analysis revealed 4 major NCNs: Anterior default-mode network (DMN), posterior DMN, salience network, and right central executive network (CEN). In fMRI data, the integrity of the posterior DMN was found to be significantly reduced in both patient groups relative to controls. In the AD group the anterior DMN and CEN appeared to be additionally affected. In PET data, only the integrity of the posterior DMN in patients with AD was reduced, whereas 3 remaining networks appeared to be affected only in patients with bvFTD. In a logistic regression analysis, the integrity of the anterior DMN as measured with PET alone accurately differentiated between the patient groups. A correlation between indices of 2 imaging modalities was low overall. Conclusion: FMRI and 18F-FDG PET capture partly different aspects of network integrity. A higher disease specificity for NCNs as derived from PET data supports metabolic connectivity imaging as a promising diagnostic tool.
CRIS-Team Scopus Importer:2022-11-28
Keywords: Alzheimer disease; Frontotemporal dementia; Multimodal neuroimaging; PET; Resting-state networks