Abstract
BACKGROUND: The assessment of dynamic changes in the cerebral glucose metabolism through a single PET scan holds significant promise for advancing our knowledge of brain function in both health and disease. Unlike fMRI, functional positron emission tomography (fPET) using [18F] Fludeoxyglucose ([18F]FDG) offers a measure of neuronal activity independent of neurovascular coupling [1,2]. However, the necessity for an arterial input function poses challenges, as it can be unpleasant for participants and also increases experimental complexity [1–3]. These limitations hinder the widespread adoption of fPET across various settings, including the clinical routine. AIMS & OBJECTIVES: We aimed to investigate the feasibility of conducting fPET without the need for an arterial or any other input function. METHODS: 52 healthy subjects (23.2 ± 3.3 years, 24 female) performed Tetris® during an [18F]FDG fPET scan. Data acquisition, processing and general linear model (GLM) analysis were performed as described in [4]. The cerebral metabolic rate of glucose (CMRGlu) was absolutely quantified using the Patlak plot and arterial input function, which was our gold standard. Simplified fPET parameters (percent signal change (%SC) of GLM beta values and %SC of CMRGlu) from a voxel-wise whole-brain and a region-wise analysis were compared (all p<0.05 FWE corrected cluster level following p<0.001 uncorrected voxel threshold). RESULTS: The voxel-wise analysis revealed nearly identical activation patterns for both approaches in brain regions characteristic for the Tetris® task (i.e., the occipital cortex, frontal eye field and intraparietal sulcus). The ROI-wise analysis resulted in strong correlations between %SC of beta values and %SC of CMRGlu (all r >0.998) (Fig 1). DISCUSSION & CONCLUSION: Relative to a baseline condition, fPET can enable the non-invasive assessment of task-specific changes in the cerebral glucose metabolism. Removing the requirement for an invasive (arterial) input function makes this promising neuroimaging tool more accessible for various applications, including clinical routine and research. Future work may use fPET to study other cognitive tasks, or assess the metabolic changes resulting from brain stimulation treatments [5], in both healthy participants as well as patient collectives. REFERENCES: 1.Villien M, Wey H-Y, Mandeville JB, Catana C, Polimeni JR, Sander CY, et al. Dynamic functional imaging of brain glucose utilization using fPET-FDG. NeuroImage. 2014;100: 192–199. doi:10.1016/J.NEUROIMAGE.2014.06.025 2. Hahn A, Gryglewski G, Nics L, Hienert M, Rischka L, Vraka C, et al. Quantification of task-specific glucose metabolism with constant infusion of 18F-FDG. Journal of Nuclear Medicine. 2016;57: 1933–1940. doi:10.2967/jnumed.116.176156 3. Li S, Jamadar SD, Ward PGD, Premaratne M, Egan GF, Chen Z. Analysis of continuous infusion functional PET (fPET) in the human brain. NeuroImage. 2020;213: 116720. doi:10.1016/j.neuroimage.2020.116720 4. Hahn A, Breakspear M, Rischka L, Wadsak W, Godbersen GM, Pichler V, et al. Reconfiguration of functional brain networks and metabolic cost converge during task performance. eLife. 2020;9. doi:10.7554/eLife.52443 5. Murphy KR, Farrell JS, Gomez JL, Stedman QG, Li N, Leung SA, et al. A tool for monitoring cell type– specific focused ultrasound neuromodulation and control of chronic epilepsy. Proceedings of the National Academy of Sciences. 2022;119: e2206828119. doi:10.1073/PNAS.2206828119