Noninvasive quantification of cerebrovascular pressure changes using 4D Flow MRI

Hemodynamic alterations are indicative of cerebrovascular disease. However, the narrow and tortuous cerebrovasculature complicates image-based assessment, especially when quantifying relative pressure. Here, we present a systematic evaluation of image-based cerebrovascular relative pressure mapping, investigating the accuracy of the routinely used reduced Bernoulli (RB), the extended unsteady Bernoulli (UB), and the full-field virtual work-energy relative pressure ( $$ WERP) method.

Patient-specific in silico models were used to generate synthetic cerebrovascular 4D Flow MRI, with RB, UB, and $$ WERP performance quantified as a function of spatiotemporal sampling and image noise. Cerebrovascular relative pressures were also derived in 4D Flow MRI from healthy volunteers ( $$ ), acquired at two spatial resolutions (dx = 1.1 and 0.8 mm).

The in silico analysis indicate that accurate relative pressure estimations are inherently coupled to spatial sampling: at dx = 1.0 mm high errors are reported for all methods; at dx = 0.5 mm $$ WERP recovers relative pressures at a mean error of 0.02 ± 0.25 mm Hg, while errors remain higher for RB and UB (mean error of -2.18 ± 1.91 and -2.18 ± 1.87 mm Hg, respectively). The dependence on spatial sampling is also indicated in vivo, albeit with higher correlative dependence between resolutions using $$ WERP (k = 0.64, R² = 0.81 for dx = 1.1 vs. 0.8 mm) than with RB or UB (k = 0.04, R² = 0.03, and k = 0.07, R² = 0.07, respectively).

Image-based full-field methods such as $$ WERP enable cerebrovascular relative pressure mapping; however, accuracy is directly dependent on utilized spatial resolution.