A generalized signal model for dual-module velocity-selective arterial spin labeling

Area of Science:

• Magnetic Resonance Imaging
• Neuroimaging
• Physiology

Background:

• Arterial spin labeling (ASL) is a non-invasive MRI technique for measuring cerebral blood flow (CBF).
• Velocity-selective ASL (VSASL) enhances specificity by using velocity-selective pulses to label or suppress spins.
• Dual-module VSASL (dm-VSASL) employs both labeling and vascular crushing modules for improved accuracy.

Purpose of the Study:

• To develop a generalized signal model for dm-VSASL.
• To integrate arbitrary saturation and inversion profiles into the model.
• To enable accurate assessment and comparison of realistic dm-VSASL implementations.

Main Methods:

• Extended a mathematical framework for single-module VSASL to dm-VSASL.
• Modeled realistic velocity-selective profiles for labeling and vascular crushing modules.
• Derived expressions for magnetization difference, arterial delivery functions, labeling efficiency, and CBF estimation error.

Main Results:

• The model accurately predicts signals for ideal velocity-selective profiles.
• Realistic profiles introduce CBF-dependent estimation errors, particularly with velocity-selective inversion (VSI) and velocity-selective saturation (VSS) combinations.
• Minimizing errors requires specific cutoff velocity choices; VSI labeling is more sensitive to field inhomogeneities than VSS.

Conclusions:

• The proposed signal model facilitates accurate performance assessment of dm-VSASL.
• It enables improved quantification of cerebral blood flow (CBF) measures using dm-VSASL.
• Researchers can better compare and optimize realistic dm-VSASL techniques.