Quantitative phase contrast MRI of penetrating arteries in centrum semiovale at 7T

Abstract Pathological changes of penetrating arteries (PA) within the centrum semiovale is an important contributing factor of cerebral small vessel disease (SVD). However, quantitative characterization of the PAs remains challenging due to their sub-voxel sizes. Here, we proposed a Model-based Analysis of Complex Difference images (MACD) of phase contrast MRI capable of measuring the mean velocities ( v mean ), diameters ( D ), and volume flow rates (VFR) of PAs without contamination from neighboring static tissues at 7 T. Simulation, phantom and in vivo studies were performed to evaluate the reproducibility and errors of the proposed method. For comparison, a Model-based Analysis of Phase difference images (MAP) was also carried out in the simulation. The proposed MACD analysis approach was applied in vivo to study the age dependence of PA properties in healthy subjects between 21 and 55 years old. Simulation showed that our proposed MACD approach yielded smaller errors than MAP, with errors increasing at lower velocities and diameters for both methods. In the phantom study, errors of the MACD-derived v mean , D , and VFR were ≤20% of their true values when v mean ≥ 1 cm/s and similar at different spatial resolutions. On the other hand, errors of the uncorrected apparent velocities were 24–60% and depended strongly on voxel size. The MACD errors linearly increased with the angle (α) between the vessel and slice normal direction at α ≤ 2° but remained almost constant at larger α. Results of the in vivo studies showed that the coefficients of repeatability for v mean , D , and VFR for PAs with α = 0° were 0.67 cm/s, 0.060 mm, and 0.067 mm 3 /s, respectively. No significant age dependence was found for the number, v mean , D , and VFR of PAs. The mean v mean , D , and VFR over all PAs with α = 0° were 1.79 ± 0.62 cm/s, 0.17 ± 0.05 mm, and 0.36 ± 0.18 mm 3 /s, respectively. Quantitative measurements of PAs with the MACD method may serve as a useful tool for illuminating the vascular pathology in cerebral SVD.