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Abstract #3291

Numerical Approximation to the General Kinetic Model for ASL Quantification

Nam Gyun Lee1, Ahsan Javed2, Terrence R. Jao1, and Krishna S. Nayak2
1Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, 2Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States

We propose a numerical approximation to Buxton's general kinetic model (GKM) for ASL quantification that will enable greater flexibility in ASL acquisition methods. The proposed method combines the Bloch-McConnell equations with the flow effects and hence model the effects of flow simultaneously with magnetization transfer, T2 effects, off-resonance, and irregular timing of labeling. These can be solved using Jaynes’ matrix formalism. The proposed approximation is compared with GKM using simulations for PASL, PCASL, steady-pulse ASL, and MR fingerprinting ASL. Accuracy of the approximation is studied as a function of a key “time interval” parameter using Monte-Carlo simulations.

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