A preliminary study of the feasibility of glucose chemical exchange saturation transfer MRI at 3T for bladder cancer

Objectives To optimize glucose chemical exchange saturation transfer (glucoCEST) MRI acquisition parameters for bladder imaging at 3.0 T through phantom experiments, and to evaluate its preliminary feasibility as a noninvasive molecular imaging biomarker for characterizing altered tumor glucose metabolism and detecting bladder cancer (BCa) in a pilot clinical cohort. Methods D-glucose phantoms with varying concentrations (6.5-100 mmol/L) and pH levels (6.4, 7.4, 8.4) were scanned using a 3.0 T scanner to systematically characterize CEST signal dependencies. Acquisition parameters were optimized by varying saturation amplitude (B 1,rms =0.5-2 µT), saturation duration (T sat =1-3 s), and number of excitations (NEX = 1-2). The phantom-optimized single-shot fast spin echo CEST protocol was then prospectively applied to 20 healthy volunteers and 20 histopathologically confirmed BCa patients. The B 0 -corrected magnetization transfer ratio asymmetry (MTR asym ) at 1.2 ppm was measured within regions of interest (ROIs) delineated on bladder tumors, normal bladder walls of patients, and healthy control walls. Statistical comparisons were performed using the Kruskal-Wallis test followed by Dunn’s post-hoc with Bonferroni correction. P < 0.05 was considered statistically significant. Results Phantom experiments showed that MTR asym (1.2 ppm) increased with glucose concentration but decreased with increasing pH. A saturation power of 2.0 µT and duration of 1 s provided an optimal CEST signal with an acceptable scan time when NEX = 1. Bladder tumors demonstrated significantly higher MTR asym values (2.25% [3.18%]) than bladder walls in healthy volunteers (-4.30% [0.68%]) and normal bladder walls in BCa patients (-3.98% [0.73%]). No significant difference was observed between healthy volunteers and normal bladder walls in BCa patients ( P = 0.231). Conclusions GlucoCEST MRI at 3.0 T is feasible for detecting BCa and is a potential noninvasive imaging biomarker of tumor glucose metabolism.