Cerebral blood volume mapping using Fourier-transform-based velocity-selective saturation pulse trains

Area of Science:

• Magnetic Resonance Imaging (MRI)
• Biomedical Engineering
• Neuroimaging

Background:

• Cerebral blood volume (CBV) measurement is crucial for understanding brain function and disease.
• Conventional velocity-selective saturation (VSS) techniques for CBV quantification can be sensitive to arterial transit time and gradient imperfections.
• Advanced pulse train designs are needed to improve the accuracy and robustness of CBV measurements.

Purpose of the Study:

• To compare Fourier-transform-based velocity-selective saturation (FT-VSS) pulse trains with conventional flow-dephasing VSS techniques for CBV quantification.
• To evaluate the performance of FT-VSS in terms of robustness to gradient imperfections and signal-to-noise ratio (SNR).

Main Methods:

• Numerical simulations and phantom studies were conducted to compare FT-VSS with double refocused hyperbolic tangent (DRHT) and 8-segment B1-insensitive rotation (BIR-8) VSS pulse trains.
• Sensitivity to gradient imperfections, such as eddy currents, was assessed.
• CBV mapping was performed in healthy subjects at 3T using FT-VSS and conventional methods with velocity-encoding gradients in three orthogonal directions.

Main Results:

• FT-VSS pulse trains demonstrated superior immunity to gradient imperfections in phantom studies.
• Compared to DRHT and BIR-8, FT-VSS yielded more robust CBV results across different encoding directions, with reduced artifacts and improved temporal SNR.
• Average CBV values for gray and white matter measured with FT-VSS were consistent with literature values (5.3 mL/100 g and 2.3 mL/100 g, respectively).

Conclusions:

• FT-VSS pulse trains offer significant advantages for absolute CBV quantification over existing flow-dephasing VSS methods.
• Enhanced immunity to gradient imperfections and effective tissue background suppression contribute to more robust CBV measurements and higher SNR with FT-VSS.
• FT-VSS represents a promising advancement for accurate and reliable CBV assessment in neuroimaging.