Dynamic functional imaging of brain glucose utilization using fPET-FDG

Abstract

Glucose is the principal source of energy for the brain and yet the dynamic response of glucose utilization to changes in brain activity is still not fully understood. Positron emission tomography (PET) allows quantitative measurement of glucose metabolism using 2-[(18)F]-fluorodeoxyglucose (FDG). However, FDG PET in its current form provides an integral (or average) of glucose consumption over tens of minutes and lacks the temporal information to capture physiological alterations associated with changes in brain activity induced by tasks or drug challenges. Traditionally, changes in glucose utilization are inferred by comparing two separate scans, which significantly limits the utility of the method. We report a novel method to track changes in FDG metabolism dynamically, with higher temporal resolution than exists to date and within a single session. Using a constant infusion of FDG, we demonstrate that our technique (termed fPET-FDG) can be used in an analysis pipeline similar to fMRI to define within-session differential metabolic responses. We use visual stimulation to demonstrate the feasibility of this method. This new method has a great potential to be used in research protocols and clinical settings since fPET-FDG imaging can be performed with most PET scanners and data acquisition and analysis are straightforward. fPET-FDG is a highly complementary technique to MRI and provides a rich new way to observe functional changes in brain metabolism.

Keywords: 2-[(18)F]-fluorodeoxyglucose (FDG); Glucose utilization; MR/PET; PET; Visual stimulus.

Figure 1. fPET-FDG experimental design

A) fPET-FDG experimental design for a 90 minutes experiment during visual paradigm alternating between a full checkerboard and left and right half checkerboard, B) fPET-FDG signal in the occipital ROI (red), defined as the voxels activated during the full checkerboard paradigm, and in the frontal ROI (black) in kBq/cc, the GLM used in the analysis in shown in black C) FDG signal in the occipital ROI after removing the baseline term, the black line represents the model we used to discriminates the slope changes for each stimulus.

Figure 2. Radioactivity concentration in the venous blood plasma and average time activity curve and derivative of the FDG signal in the whole brain

(A) Venous blood was collected every 10 minutes in the arm of our 3 subjects during the 90 minute experiments. The interpolated average radioactivity concentration in the venous blood plasma of our 3 subjects (mean ± std) is shown. (B) The normalized time activity curve in the whole brain for the 3 subjects shows a linear increase during the entire 90 minutes experiment. (C) The smoothed derivative of the normalized time activity curve in the whole brain for the 3 subjects shows that after around 30 minutes the derivative of the signal is stable.

Figure 3. Average CMR_glu map

Average CMR_glu map in μmol/100g/min (scale from 0 to 0.6) across the 3 subjects. The CMR_glu maps were derived from the slope of the TAC, normalized to venous blood plasma radioactivity concentration (in min⁻¹), multiplied by the glucose measurement (mmol/L) and divided by the lumped constant (0.89).

Figure 4. Comparison of simulated and experimental responses with exponential fitting of the data

A) Simulation of the effect of a brief change in k3 on the derivative of the FDG signal in the course of the infusion protocol. The red line represents the derivative of the FDG signal and the blue line represents the metabolized FDG. (B) Normalized FDG signal change during the 10 minute full checkerboard for the 3 individual subjects (dashed lines) and the average response (red line). (C) Average normalized FDG signal change during the 10 minute full checkerboard for the 3 individual subjects (red line) with an exponential fit for the increase in FDG signal after the beginning of the activation period ( blue, R² = 0.96, τ = 4.9 min) and for the decrease in FDG signal after the end of the activation period (green, R² = 0.98, τ = 5.6min). Exponential fitting was accomplished using GraphPad Prism® software (Prism6, GraphPad Software Inc., La Jolla, CA, USA).

Figure 5. fPET-FDG activations maps for a single subject

Statistical maps (T-score > 6) of the activations observed for a single subject during the two blocks of 10 minutes full-field checkerboard presentation, the single 5 minute block of left hemi-field checkerboard and the single 5 minute block of right hemi-field checkerboard.

Figure 6. Fixed-effects group analysis

(top and bottom left) Percent signal change maps obtained for the fixed-effects group analysis (n = 3) during the single 5 minute block of left hemi-field checkerboard, the single 5 minute block of right hemi-field checkerboard and the two blocks of 10 minutes full-field checkerboard; (bottom right) Percent signal change values obtained in the a priori anatomical V1 ROI from the Jülich histological atlas for the fixed-effect group analysis (n = 3) during the two blocks of 10 minutes full-field checkerboard, the single 5 minute block of left hemi-field checkerboard and the single 5 minute block of right hemi-field checkerboard.

Figure 7. Non-human primate experiment

The red line shows a linear increase of FDG signal in the grey matter of one anesthetized baboon during the 50 minute constant infusion. A hypercapnic challenge (7% CO₂) was administered between 30 and 40 minutes (shaded area) and ASL was acquired around the challenge to measures changes in CBF. The blue line shows an increase in average percent signal change in CBF measured in the grey matter using ASL during the hypercapnic challenge, followed by a decrease in CBF after the end of the hypercapnic challenge.