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

Area of Science:

• Medical Imaging
• Biophysics
• Pharmacokinetics

Background:

• The arterial input function (AIF) is crucial for pharmacokinetic modeling, representing time-dependent arterial contrast agent (CA) concentration.
• Accurate AIF estimation is vital for reliable DCE-MRI analysis.

Purpose of the Study:

• To develop a novel method for estimating AIF from DCE-MRI data.
• To compensate for signal enhancement caused by blood flow (inflow effect).

Main Methods:

• Simulated time-intensity curves (TICs) with varying excitation pulses to model flow.
• Conducted phantom experiments with controlled flow velocity.
• Utilized dynamic fast spoiled gradient echo (FSPGR) sequences at 3T MRI.
• Developed a method to estimate the number of excitation pulses experienced by spins.

Main Results:

• The proposed method accurately estimated CA concentration, with median differences from reference values as low as -0.00015 mmol/L.
• Estimated flow velocities in phantom experiments were within 10% of the reference value.
• The method demonstrated robust performance across a range of pulse numbers and CA concentrations.

Conclusions:

• The novel method effectively corrects MRI signal artifacts due to the inflow effect.
• This technique enhances the accuracy of AIF estimation in DCE-MRI.
• Improved AIF estimation facilitates more precise pharmacokinetic modeling.