Estimating the arterial input function from dynamic contrast-enhanced MRI data with compensation for flow enhancement (I)

Abstract

Background: The arterial input function (AIF) represents the time-dependent arterial contrast agent (CA) concentration that is used in pharmacokinetic modeling. Purpose: To develop a novel method for estimating the AIF from dynamic contrast-enhanced (DCE-) MRI data, while compensating for flow enhancement. Study Type: Signal simulation and phantom measurements. Phantom Model: Time–intensity curves (TICs) were simulated for different numbers of excitation pulses modeling flow effects. A phantom experiment was performed in which a solution (without CA) was passed through a straight tube, at constant flow velocity. Field Strength/Sequence: Dynamic fast spoiled gradient echo (FSPGRs) at 3T MRI, both in the simulations and in the phantom experiment. TICs were generated for a duration of 373 seconds and sampled at intervals of 1.247 seconds (300 timepoints). Assessment: The proposed method first estimates the number of pulses that spins have received, and then uses this knowledge to accurately estimate the CA concentration. Statistical Tests: The difference between the median of the estimated number of pulses and the true value was deter- mined, as well as the interquartile range (IQR) of the estimations. The estimated CA concentrations were evaluated in the same way. The estimated number of pulses was also used to calculate flow velocity. Results: The difference between the median estimated and reference number of pulses varied from –0.005 to –1.371 (corresponding IQRs: 0.853 and 48.377) at true values of 10 and 180 pulses, respectively. The difference between the median estimated CA concentration and the reference value varied from –0.00015 to 0.00306 mmol/L (corresponding IQRs: 0.01989 and 1.51013 mmol/L) at true values of 0.5 and 8.0 mmol/l, respectively, at an intermediate value of 100 pulses. The estimated flow velocities in the phantom were within 10% of the reference value. Data Conclusion: The proposed method accurately corrects the MRI signal affected by the inflow effect. Level of Evidence: 1 Technical Efficacy: Stage 1