Single-shot multiparametric MRI for separating <i>T₂</i> effects from dynamic glucose-enhanced contrast

<b>Background:</b> Glucose is a central substrate in cellular metabolism and serves as a non-invasive biomarker for pathological processes. Dynamic glucose-enhanced (DGE) MRI based on chemical exchange saturation transfer (CEST) offers a promising tool for mapping glucose uptake, but its quantification is confounded by glucose-induced changes in <i>T₂</i> relaxation in addition to glucose concentration. <b>Methods:</b> We developed a single-shot multiparametric CEST (MP-CEST) MRI sequence based on multi-echo spatiotemporal encoding (SPEN), enabling the simultaneous acquisition of <i>T₂</i> and saturation-weighted proton density (PD) maps within a single scan. To correct for <i>T₂</i> -related confounding effects in glucoCEST quantification, a two-step correction strategy was employed. First, the saturation-weighted PD maps, which mitigate <i>T₂</i> -dependent signal attenuation during image acquisition, were used to reconstruct the Z-spectrum, thereby providing a more accurate representation of the true saturation signal amplitude. Second, calibration curves derived from Bloch-McConnell simulations were applied in combination with the simultaneously acquired <i>T₂</i> maps to compensate for spillover effects in the Z-spectrum, thereby improving glucose-specific CEST contrast. The full framework was validated through phantom experiments and <i>in vivo</i> studies in rat brain and tumor xenograft models. Quantitative performance was evaluated by computing the Pearson correlation between DGE signals and <i>T₂</i> values before and after correction, as well as by comparing fitted <i>T₂</i> and PD values with reference maps. <b>Results:</b> Phantom experiments demonstrated high accuracy in PD and <i>T₂</i> quantification (R² > 0.99). <i>In vivo</i> studies in rat brain and tumor xenografts showed that the proposed correction method significantly reduced the correlation between DGE signals and <i>T₂</i> values, improving the specificity of glucose-related contrast. In addition, <i>T₂</i> maps provided complementary structural and physiological information relevant to tumor heterogeneity and tissue microstructure. <b>Conclusions:</b> The proposed MP-CEST approach improves the robustness and accuracy of DGE quantification, offering a more comprehensive metabolic imaging framework applicable to both oncological and neurological research.