Non-invasive quantification of cerebral glucose metabolism using Gjedde-Patlak plot and image-derived input function from the aorta

• Published in: NeuroImage (Orlando, Fla.) Vol. 253; p. 119079
• Main Authors: Henriksen, Alexander Cuculiza, Lonsdale, Markus Nowak, Fuglø, Dan, Kondziella, Daniel, Nersesjan, Vardan, Marner, Lisbeth
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.06.2022; Elsevier Limited; Elsevier
• Subjects: [18F]FDG; Algorithms; Aorta; Aorta - diagnostic imaging; Aorta - metabolism; Blood levels; Brain; Brain - diagnostic imaging; Brain - metabolism; Cannulation; Cerebellum; Cerebral glucose metabolism; CMRglc; Coronary vessels; Cortex (frontal); Fluorodeoxyglucose F18 - metabolism; Glucose; Glucose - metabolism; Hippocampus; Humans; Metabolic rate; Metabolism; PET; Plasma; Positron emission tomography; Positron-Emission Tomography - methods; Radiopharmaceuticals - metabolism; Software; Values; Veins & arteries; United States > US; Chicago Illinois; [18F]FDG; Brain; Positron emission tomography; CMRglc; PET; Cerebral glucose metabolism; [F]FDG
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2022.119079

We aimed at evaluating a Gjedde-Patlak plot and non-invasive image-derived input functions (IDIF) from the aorta to quantify cerebral glucose metabolic rate (CMRglc) in comparison to the reference standard based on sampling the arterial input function (AIF). Six healthy subjects received 200 MBq [18F]FDG simultaneously with the initiation of a three-part dynamic PET recording consisting of a 15 min-recording of the aorta, a 40 min-recording of the brain and finally 2 min-recording of the aorta. Simultaneously, the arterial 18F concentration was measured via arterial cannulation. Regions of interest were drawn in the aorta and the brain and time-activity curves extracted. The IDIF was obtained by fitting a triple exponential function to the aorta time-activity curve after the initial peak including the late aorta frame, thereby interpolating the arterial blood activity concentration during the brain scan. CMRglc was calculated from Gjedde-Patlak plots using AIF and IDIF, respectively and the predictive value was examined. Results from frontal cortex, insula, hippocampus and cerebellum were compared by paired t-test and agreement between the methods was analyzed by Bland-Altman plot statistics. There was a strong linear relationship and an excellent agreement between the methods (mean±SD of CMRglcIDIF (μmol 100 g−1 min−1), mean difference, mean relative difference, 95% limits of agreement): frontal cortex: 30.8 ± 3.3, 0.5, 2.2%, [-1,6:2.5], insula: 25.4 ± 2.2, 0.4, 2.4%, [-1.4:2.2], hippocampus: 16.9 ± 1.2, 0.4, 3.8%, [-1.1:2.0] and cerebellum: 23.4 ± 1.9, 0.5, 3.1%, [-1.4:2.5]). We found excellent agreement between CMRglc obtained with an IDIF from the aorta and the reference standard with AIF. A non-invasive three-part dynamic [18F]FDG PET recording is feasible as a non-invasive alternative for reliable quantification of cerebral glucose metabolism in all scanner systems. This is useful in patients with presumed global cerebral changes owing to systemic disease or for the monitoring of treatment effects.