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Abstract #1354

Double-step R1rho-based LOrentzian Fitting (DROF): a new CEST analysis approach and its comparison with existing methods

Huabin Zhang1,2, Jiawen Wang1, Shihao Zeng1, Pei Cai1, Ziyan Wang1, Bensheng Qiu2, and Jianpan Huang1,3
1Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong, China, 2Medical Imaging Center, Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China, 3Tam Wing Fan Neuroimaging Research Laboratory, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China

Synopsis

Keywords: CEST / APT / NOE, CEST / APT / NOE

Motivation: At 3T MRI, reliable quantification of amide, guan, and rNOE is hindered by broad background and fitting dependency on initial values and boundary conditions.

Goal(s): To propose a robust CEST analysis method for extracting 5-pool parameters at 3T and a quantitative metric to evaluate the performance of existing fitting methods.

Approach: A double-step R1rho-based LOrentzian Fitting (DROF) method with random initial guesses was developed for CEST analysis. The accuracy and robustness of DROF were assessed on both simulation and in-vivo human data at 3T and compared with existing methods.

Results: The new method demonstrates improved specificity and stability compared to other methods.

Impact: We proposed a double-step R1rho-based LOrentzian Fitting (DROF) method for extracting 5-pool CEST parameters at 3T. DROF exhibits enhanced specificity and stability compared to other methods, suggesting its potential to promote wider CEST applications at 3T.

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Keywords