Purpose
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 (νWERP) method.
Methods
Patient‐specific in silico models were used to generate synthetic cerebrovascular 4D Flow MRI, with RB, UB, and νWERP performance quantified as a function of spatiotemporal sampling and image noise. Cerebrovascular relative pressures were also derived in 4D Flow MRI from healthy volunteers (n=8), acquired at two spatial resolutions (dx = 1.1 and 0.8 mm).
Results
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 νWERP 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 νWERP (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).
Conclusion
Image‐based full‐field methods such as νWERP enable cerebrovascular relative pressure mapping; however, accuracy is directly dependent on utilized spatial resolution.