Keywords: Arterial Spin Labelling, Arterial spin labelling, Simulation
Motivation: We identified a gap in understanding multi-tag Time-SLIP MRI dynamics, crucial for advanced perfusion analysis, particularly in varying physiological and pathological states.
Goal(s): Our goal was to develop a comprehensive simulation tool to accurately predict signal changes in multi-tag Time-SLIP ASL MRI across diverse flow conditions.
Approach: We employed MATLAB to simulate numerically non-selective and selective multi-tag Time-SLIP pulse sequences, applying Bloch equations to model tissue-specific magnetization and blood flow perfusion dynamics.
Results: Simulations showed distinct magnetization patterns between odd and even pulse tags, aligning with physiological flow rates.
Impact: This simulation tool enables researchers to customize Time-SLIP MRI protocols for detailed study of fluid dynamics across the body, from blood to CSF flow. It provides a solid foundation for developing more comprehensive ASL-related simulations.
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