PURPOSE: Nuclear overhauser enhancement (NOE) mediated chemical exchange saturation transfer (CEST) effect at -3.5 ppm from water is attributed to mobile macromolecular components with finite linewidth^{1, 2}. It has been shown that the NOE-mediate CEST imaging has clinical interests in diagnosing tumors^3-6. Fast and accurate quantification of NOE effect is crucial for its translation to clinical applications. Previously, NOE effect has been quantified by the Lorentzian difference (LD) analysis³, multiple-pool Lorentzian fit⁷, three-point method⁸, and asymmetric analysis (MTR_asym)⁵. However, both the LD analysis and multiple-pool Lorentzian fit require the acquisition of the whole Z-spectrum which takes a long imaging time, and rely on the initial values of the fitting parameters; The three-point method may underestimate the NOE effect⁹; The asymmetric analysis of NOE effect is fast and the data processing is simple, but it has contamination from the downfield amide proton transfer (APT) effect at 3.5 ppm. In this abstract, we provide a new NOE quantification method using the asymmetric analysis of CEST signals acquired with 2pi saturation pulses (2pi-CEST) which is also fast but has reduced contamination from the APT effect.
METHODS: The 2pi-CEST saturation block contains a series of Gaussian RF saturation pulses with pulse duration of 13ms and pulse repetition time (PTR) of 72.2ms (corresponding to average saturation power of 1µT) and with total saturation time of 5s (corresponding to 69 PTR). The conventional continuous-wave (CW)-CEST was also studied to compare with the asymmetric analysis of 2pi-CEST. The saturation block of the CW-CEST contains a 5s rectangular RF pulse with saturation power of 1µT. Both the 2pi- and CW-CEST saturation blocks are followed by single-shot spin-echo echo planar imaging (SE-EPI) readout and a recovery time of 2s. Previously, an inverse subtraction analysis with correction of apparent water longitudinal relaxation rate (R_1obs), termed apparent exchange-dependent relaxation (AREX), has been used to improve the specificity in quantifying CEST effect ¹⁰. Here, we combine the AREX with asymmetric analysis of CEST signals, termed AREX_asym, to quantify the NOE effect,
$$ AREX_{asym}(Δω)=(S_0/S_+(Δω) - S_0/S\_(Δω))R_{1obs} (1+f_m) $$ (1)
where (+) represents the offset of the upfield NOE component and (-) is the offset on the symmetrically opposite side of the water peak. S₀ is the control signal acquired without RF saturation; Δω is the RF saturation pulse frequency offset from water; f_m is macromolecular pool size ratio.
A two-pool (solute and water) model simulations of coupled Bloch equations were performed to evaluate the dependence of the asymmetric analysis of CW-CEST signals (AREX_{asym_cw}) and the asymmetric analysis of 2pi-CEST signals (AREX_{asym_2pi}) on the exchange/coupling rate (k_sw) and the solute T₂ (T_2s). Experiments were performed on three rat brains bearing 9L tumors to evaluate the ability of the asymmetric analysis of 2pi-CEST to remove the contamination from APT. All measurements were performed on a Varian 9.4 T magnet with a 38-mm Litz RF coil. Z-spectra were acquired with RF offsets from -2000 to 2000 Hz with a step of 50 Hz (-5 to 5ppm on 9.4 T). Control signal was obtained by setting the RF offset to 100000 Hz (250ppm on 9.4T). R_1obs and f_m were obtained using a selective inversion recovery (SIR) quantitative MT method¹¹. All images were acquired with matrix size 64 ´ 64, field of view 30 mm ´ 30 mm, and one average. All animal procedures were approved by the local Animal Care and Usage Committee.
RESULTS:
Fig. 1 shows the simulated AREX_{asym_CW}, AREX_{asym_2pi}, and AREX_{asym_2pi}/AREX_{asym_CW} as a function of k_sw and T_2s, respectively. Compared with the AREX_{asym_CW}, AREX_{asym_2pi} is less sensitive to slow-intermediate exchanging pools with relatively long T_2s (e.g., amide at 3.5ppm, guanidino amine at 2ppm), but is sensitive to short T_2s components with slow exchange/coupling rate (e.g. the NOE at 3.5ppm) and fast exchanging pools with relatively long T_2s (e.g. lysine amine at 3ppm). This simulation suggests that the AREX_{asym_2pi} can be applied to reduce the contamination from the APT effect in quantifying the NOE effect. Fig. 2 shows the averaged CW-, 2pi-CEST Z-spectrum as well as AREX_{asym_CW} and AREX_{asym_2pi} spectra from the tumor and the contralateral normal tissue. Note that although the APT at 3.5ppm and amine at 2ppm are apparent in the CW-CEST spectra, they become weak in the 2pi-CEST spectra; Also note that a dip at -3.5ppm is overlaid on a broad NOE peak on the AREX_{asym_CW} spectra which is due to the contamination from the APT effect, but not on the AREX_{asym_2pi} spectra. Fig. 3 shows the statistical differences of AREX_{asym_CW}(-3.5ppm) and AREX_{asym_2pi}(-3.5ppm) between tumor and the contralateral normal tissue. Fig. 4 shows the maps of the AREX_{asym_CW}(-3.5ppm) and AREX_{asym_2pi}(-3.5ppm) from a representative rat brain.

DISCUSSION AND CONCLUSION:
The asymmetric analysis of 2pi-CEST signals only needs the acquisition of the label, reference, and control signals which is fast and easy to be performed. By reducing the APT effect, it is more accuracy than the conventional asymmetric analysis of CEST signals in quantifying the NOE effect. Asymmetric MT effect¹² and the CEST effect from fast exchanging pools are other contamination factors. But they should be relatively small compared with the NOE effect acquired with low saturation powers.

Acknowledgements

The authors acknowledge grant support from NIH (R21 AR074261, R03 EB029078, and R01 EB029443).