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Numerical approximation to the general kinetic model for ASL quantification
Author(s) -
Lee Nam G.,
Javed Ahsan,
Jao Terrence R.,
Nayak Krishna S.
Publication year - 2020
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.28304
Subject(s) - arterial spin labeling , magnetization transfer , approximation error , physics , steady state free precession imaging , algorithm , nuclear magnetic resonance , computational physics , mathematics , cerebral blood flow , magnetic resonance imaging , medicine , cardiology , radiology
Purpose To develop a numerical approximation to the general kinetic model for arterial spin labeling (ASL) quantification that will enable greater flexibility in ASL acquisition methods. Theory The Bloch‐McConnell equations are extended to include the effects of single‐compartment inflow and outflow on both the transverse and longitudinal magnetization. These can be solved using an extension of Jaynes’ matrix formalism with piecewise constant approximation of incoming labeled arterial flow and a clearance operator for outgoing venous flow. Methods The proposed numerical approximation is compared with the general kinetic model using simulations of pulsed labeling and pseudo‐continuous labeling and a broad range of transit time and bolus duration for tissue blood flow of 0.6 mL/g/min. Accuracy of the approximation is studied as a function of the timestep using Monte‐Carlo simulations. Three additional scenarios are demonstrated: (1) steady‐pulsed ASL, (2) MR fingerprinting ASL, and (3) balanced SSFP and spoiled gradient‐echo sequences. Results The proposed approximation was found to be arbitrarily accurate for pulsed labeling and pseudo‐continuous labeling. The pulsed labeling/pseudo‐continuous labeling approximation error compared with the general kinetic model was less than 0.002% (<0.002%) and less than 0.05% (<0.05%) for timesteps of 3 ms and 35 ms, respectively. The proposed approximation matched well with customized signal expressions of steady‐pulsed ASL and MR fingerprinting ASL. The simulations of simultaneous modeling of flow, T 2 , and magnetization transfer showed an increase in steady‐state balanced SSFP and spoiled gradient signals. Conclusion We demonstrate a numerical approximation of the “Bloch–McConnell flow” equations that enables arbitrarily accurate modeling of pulsed ASL and pseudo‐continuous labeling signals comparable to the general kinetic model. This enables increased flexibility in the experiment design for quantitative ASL.