PURPOSE

A relayed nuclear Overhauser enhancement (rNOE) saturation transfer effect at around -1.6 ppm from water, termed NOE(-1.6), was previously reported in rat and human brain¹. Recently, we found that the NOE(-1.6) signal from rat brain changes significantly with intake of different gases (i.e. air, O₂, and N₂O), suggesting that the NOE(-1.6) signal may be related to cerebrovascular changes². Two other publications also indicated that the NOE(-1.6) signal may include significant contributions from blood^3,4. In this work, we evaluated the contribution of blood to the NOE(-1.6) signal using two blood suppression approaches and ex vivo blood samples.

METHODS

All measurements were performed on a pre-clinical Varian 9.4T MRI. Chemical exchange saturation transfer (CEST) measurements were obtained by applying a continuous wave CEST sequence with a 5s irradiation pulse followed by the SE-EPI readout. Z-spectra were acquired with RF offsets from -10 to 10ppm and an RF power of 1µT. Control signals (S₀) were acquired without RF irradiation. Five rats were anesthetized with 2% isoflurane and 98% O₂ for both induction and maintenance. To suppress the intravascular signal, two approaches were compared: (1) signal acquisition with a diffusion-weighting of b = 400s/mm² to reduce intravoxel incoherent motion (IVIM) effects; (2) intravascular injection of 5mg/kg monocrystalline iron oxide nanoparticle (MION) to reduce intravascular signals. In vitro blood samples were collected using a syringe containing lyophilized heparin, and moved quickly to a sealed tube. All animal procedures were approved by the Animal Care and Use Committee of Vanderbilt University Medical Center. A multiple-pool (water, amide at 3.5ppm, amine at 2ppm, NOE at -1.6 and -3.5ppm, and semi-solid MT at -2.3ppm) Lorentzian fitting of each Z-spectrum was performed to isolate each peak. We used apparent exchange-dependent relaxation (AREX) metrics to specifically quantify NOE and CEST effects.

RESULTS

Fig. 1 shows the results of the in vivo experiment with diffusion weighting. Note that although there are significant differences between the control signals (Fig. 1f) acquired with/without diffusion weighting, due to the loss of intravascular signals and diffusion effect, there are no statistical differences between the AREX values of the CEST and NOE data acquired with/without diffusion weighting (Fig. 1c-1e). Fig. 2 shows results of the ex vivo experiment on blood. Note that the fitted NOE(-1.6) from ex vivo blood (7.0%) is lower than that from the in vivo experiments (10.1% ± 0.6%, b = 0s/mm² in Fig. 1d). Fig. 3 shows results of the in vivo experiment acquired before/after injection of MION. The control signals (Fig. 3f) decrease significantly, indicating successful injection of MION and increased transverse relaxation. Note that although the fitted NOE(-1.6) (Fig. 3d) decreases significantly by 54.6%, the NOE(-3.5) has no significant changes and the amide signal only decreases significantly by 14.6%.

DISCUSSION AND CONCLUSION

Fig. 1d also suggests a decrease of the mean AREX value for NOE(-1.6) with diffusion weighting, although it is not statistically significant. However, it only deceases by 11.9 % (from 10.1 %s^-1 to 8.9 %s^-1). Considering the relatively small volume of blood in the brain, the in vivo experiments with diffusion weighting and the ex vivo experiments both suggest that the NOE(-1.6) is not mainly from the blood. MION particles in flowing blood can not only suppress intravascular and perivascular signals, but add a fluctuating field to brain parenchyma which may decrease the NOE dipolar correlation time and thus decrease the NOE effect.

Acknowledgements

No acknowledgement found.