Motion-Compensated Diffusion Imaging With Phase-Contrast for Robust Quantification of Regional Cerebral Blood Flow.

ABSTRACT Purpose To develop and evaluate a motion‐compensated diffusion imaging with phase‐contrast (MC‐DIP) technique for mitigating errors in regional cerebral blood flow (rCBF) quantification caused by physiological brain motion. Methods Diffusion‐weighted images were acquired in 11 healthy volunteers on a 3.0 T MRI system using three gradient schemes: second‐order motion‐compensated (2nd‐MC), first‐order motion‐compensated (1st‐MC), and non‐compensated (non‐MC) diffusion gradients. Absolute rCBF maps were generated for each scheme by calibrating intravoxel incoherent motion‐derived relative perfusion maps with total cerebral blood flow measured by phase‐contrast MRI. The rCBF values from the DIP methods were compared in gray and white matter with a reference arterial spin labeling (ASL) measurement. Results Both motion‐compensated schemes (2nd‐MC and 1st‐MC) provided significantly better biexponential fitting accuracy in gray matter compared with the non‐MC scheme ( p < 0.05). In white matter, however, only the 2nd‐MC scheme resulted in a significant improvement over the other methods ( p < 0.05). While rCBF values from all three DIP methods showed a strong positive correlation with ASL in gray matter ( ρ ≥ 0.82, p < 0.05), only the 2nd‐MC‐DIP method demonstrated a significant positive correlation in white matter ( ρ = 0.69, p < 0.05). Conclusion The implementation of second‐order motion compensation within the DIP framework improves fitting accuracy, enabling robust rCBF quantification.