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Quasi-steady-state CEST for rapid and quantitative lesion detection in multiple sclerosis at 3T
Huabin Zhang1, Ziyan Wang2, Shihao Zeng2
1Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China; Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
None:
Chemical Exchange Saturation Transfer (CEST) MRI has demonstrated significant value in the early diagnosis of multiple sclerosis (MS) and monitoring of remyelination. However, quantitative CEST MRI is highly susceptible to varied scan parameters and typically requires long saturation times to achieve equilibrium conditions for adequate contrast. This study investigates the use of quasi-steady-state (QUASS) CEST MRI at 3T to shorten scan time while maintaining consistent lesion contrast in MS. Numerical simulations and in vivo experiments (8 healthy volunteers and 8 MS patients) were performed to evaluate QUASS-corrected quantitative measurement. Five CEST effects including amide, CEST at 2 ppm (CEST@2ppm), magnetization transfer (MT), relayed nuclear Overhauser enhancement (rNOE), and direct water saturation (DS), were isolated using a 5-pool Lorentzian fitting. Simulations confirmed that QUASS effectively eliminates saturation time dependence and enhances the detectability of CEST@2ppm. In in vivo experiments, QUASS processing enabled high MS lesion contrast even with a 46.7 % reduction in scan time. QUASS-corrected CEST results exhibited progressively decreasing rNOE and MT contrasts across white matter (WM), normal-appearing WM (NAWM), and lesions, indicating advanced demyelination. While amide showed no significant difference between WM and NAWM, it decreased markedly in lesions, suggesting protein loss in severe demyelination. CEST@2ppm exhibited a significant decrease in lesions, reflecting dynamic microenvironmental changes throughout MS progression. The proposed QUASS CEST imaging scheme shows strong potential to provide rich quantitative information for clinical MS diagnosis and treatment evaluation.
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