Samira M. Kazan1, Michael A. Chappell2, Stephen J. Payne1
1Institute of Biomedical Engineering, University of Oxford, Oxford, Oxfordshire, UK; 2Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford, Oxford, Oxfordshire, UK
The clinical predictive power of the ASL signal is reduced by significant variability in the signal, which experimental data indicates is affected by dispersion and cardiac pulsatility in blood entering the brain. Our new physiological mass-transport model simulates the transport of the ASL signal from the tagging to imaging bands, coupled with fluid dynamics equations for flow in an elastic vessel. Our simulations indicate that cardiac pulsatility contributes up to 20% of ASL signal variability. This has implications in the choice of single or multiple inversion times, and the use of cardiac gating, in obtaining more accurate measures of CBF.
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