Towards robust glucose chemical exchange saturation transfer imaging in humans at 3 T: Arterial input function measurements and the effects of infusion time

Abstract

Dynamic glucose-enhanced (DGE) magnetic resonance imaging (MRI) has shown potential for tumor imaging using D-glucose as a biodegradable contrast agent. The DGE signal change is small at 3 T (around 1%) and accurate detection is hampered by motion. The intravenous D-glucose injection is associated with transient side effects that can indirectly generate subject movements. In this study, the aim was to study DGE arterial input functions (AIFs) in healthy volunteers at 3 T for different scanning protocols, as a step towards making the glucose chemical exchange saturation transfer (glucoCEST) protocol more robust. Two different infusion durations (1.5 and 4.0 min) and saturation frequency offsets (1.2 and 2.0 ppm) were used. The effect of subject motion on the DGE signal was studied by using motion estimates retrieved from standard retrospective motion correction to create pseudo-DGE maps, where the apparent DGE signal changes were entirely caused by motion. Furthermore, the DGE AIFs were compared with venous blood glucose levels. A significant difference (p = 0.03) between arterial baseline and postinfusion DGE signal was found after Dglucose infusion. The results indicate that the measured DGE AIF signal change depends on both motion and blood glucose concentration change, emphasizing the need for sufficient motion correction in glucoCEST imaging. Finally, we conclude that a longer infusion duration (e.g. 3-4 min) should preferably be used in glucoCEST

Motion correction for three‐dimensional chemical exchange saturation transfer imaging without direct water saturation artifacts

“…In contrast to previous studies, 11,12 the motion patterns were not only generated by a normally distributed random motion—which would basically resemble a shaking or back‐and‐forth wobbling of the head—but by performing a Gaussian random walk with additional modifiers (Section 2.3.1) to mimic the realistic situation of continuous drifts with a few abrupt movements in between. The patterns obtained in this way bear a close resemblance to the real motion observed in the 77 patient measurements (data not shown) and in previous publications, 14,15,26,27 verifying in addition also the presumed, to a certain extent, continuous and smooth motion. The parameters used in this study were of the same order of magnitude as in previous simulation studies regarding motion in CEST‐MRI (standard deviations of 0.5–1.0 pixels and 0.5–1.0°, 12 3.8 mm and 4.0°, 11 as well as 0.6 mm and 1.0° 14 ) and real in vivo measurements (up to 0.5 mm and 2.0°, 15 as well as 0.5 mm and 0.5° 14 ).…”

A numerical human brain phantom for dynamic glucose‐enhanced (DGE) MRI: On the influence of head motion at 3T

“…The '+' denotes outliers, defined as values that are more than 1.5 times the interquartile range away from the bottom or top of the box originate from the involuntary relaxation of the subject's neck muscles, leading to a translation in Z-direction and a pitch rotation similar to nodding. [53][54][55] Ventricular volume variations are caused by cardiac pulsation and loading of D-glucose 20,25,26 These effects were simulated together in Figures 4 and 5 for cases with and without glucose infusion, leading to signal variations similar to those reported in vivo at 3 T (0.25%-1.5% in tumors). 20,28,29,32 Note that development of new pulse sequences 56 or use of other sugars such as 3-ortho-methylglucose (3OMG) 57,58 or D-glucosamine (D-GlcN) 59 is expected to increase these effects.…”

“…For the tumor, a concentration of 2750 mM was assumed because of its location between GM and WM and having a higher water content. Time-dependent glucoCEST uptake curves were simulated, based on the overall shape of DGE response curves previously observed at 3 T. 13,20,32,39 A dynamic time series with an acquisition duration of 690 s and a temporal resolution of 5 s was simulated. The time series consisted of S 0 (non-saturated signal) data acquisition (20 s), baseline (20-140 s), D-glucose infusion (140-380 s), signal increase and decay (380-565 s).…”

“…23,24 Other sources of signal change may be dilatation of the lateral ventricles caused by D-glucose uptake and ventricular pulsation related to, for example, the cardiac pulsation. 20,[25][26][27] A previous study investigated the effect of motion using difference images of Z-spectra without glucose infusion to create synthetic data before and after simulated motion, also taking B 0 -fluctuations into consideration. 28 Hypo-and hyperintense signal changes of the order of 1% were observed in the vicinity of tissue boundaries, causing pseudo-DGE effects of the same order of magnitude as the DGE signal changes.…”

Imaging in translational cancer research

“…CEST imaging enables mapping of tissue pH levels via amide proton transfer CEST 155 , wherein backbone amide protons of mobile proteins and peptides provide the endogenous CEST contrast 156 . Further applications include glucose CEST (glucoCEST) 157 , to detect intercellular glucose delivery and transport; the first applications outside brain tissue, e.g., detection of ductal pancreatic adenocarcinoma 158 ; kidney assessment via renal pH levels 159 ; prostate cancer detection 160 ; and diagnosis of breast cancer via glucosamine CEST in clinical settings 161 .…”