Investigating white matter perfusion using optimal sampling strategy arterial spin labeling at 7 Tesla

Area of Science:

• Neuroimaging
• Physiology
• Magnetic Resonance Imaging

Background:

• Cerebral blood flow (CBF) is a key indicator of brain tissue health.
• Arterial spin labeling (ASL) is a noninvasive MRI technique for measuring CBF.
• Measuring white matter (WM) CBF is challenging due to low contrast-to-noise ratio compared to gray matter (GM).

Purpose of the Study:

• To investigate white matter (WM) cerebral blood flow (CBF) using ultra-high field (7T) ASL combined with an optimal sampling strategy (OSS).
• To achieve reliable WM CBF quantification within practical scan times.

Main Methods:

• A FAIR-based ASL sequence at 7 Tesla was employed.
• A real-time feedback optimal sampling strategy (OSS) technique was utilized.
• Post-label image acquisition times were iteratively optimized on a tissue- and subject-specific basis for WM CBF quantification.

Main Results:

• Reasonable CBF fits were obtained in 77% of white matter (WM) voxels.
• The average WM CBF was quantified as 16.3 ± 1.5 mL/100 g/min (excluding partial-volumed voxels).
• The optimal sampling strategy (OSS) generated acquisition schedules favoring longer inversion times (TIs) for WM compared to GM.

Conclusions:

• White matter (WM) CBF can be reliably quantified in over 75% of voxels using this 7T ASL with OSS method.
• The total preparation and scan time was reduced to 15 minutes.
• The findings suggest that longer inversion times (TIs) are beneficial for WM ASL, potentially enhancing studies of WM diseases.