4.5 Article

Noninvasive quantification of cerebrovascular pressure changes using 4D Flow MRI

Journal

MAGNETIC RESONANCE IN MEDICINE
Volume 86, Issue 6, Pages 3096-3110

Publisher

WILEY
DOI: 10.1002/mrm.28928

Keywords

4D Flow MRI; cerebrovascular; hemodynamics; patient-specific modeling; relative pressure

Funding

  1. London Medical Imaging and AI Centre for Value-Based Healthcare
  2. NIH, Ruth L. Kirschstein National Research Service Award [F30 HL140910]
  3. NIH, Northwestern -Medical Science Training Program [T32 GM815229]
  4. NIH [R01 49039]
  5. Knut och Alice Wallenbergs Stiftelse
  6. Wellcome/EPSRC Centre for Medical Engineering [WT203148/Z/16/Z]
  7. University of MichiganRackham Predoctoral Fellowship
  8. Engineering and Physical Sciences Research Council [EP/N011554/1, EP/R003866/1]
  9. Institutue of Technology and Broad Institute
  10. EPSRC [EP/N011554/1, EP/R003866/1] Funding Source: UKRI

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The study systematically evaluated the accuracy of image-based cerebrovascular relative pressure mapping, with results showing a close relationship between accurate estimations and spatial sampling. The nu WERP method demonstrated lower errors and higher correlation between resolutions, indicating its effectiveness in recovering relative pressures in cerebrovascular assessment.
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 (nu WERP) method. Methods: Patient-specific in silico models were used to generate synthetic cerebrovascular 4D Flow MRI, with RB, UB, and nu 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 (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 nu 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 nu WERP (k = 0.64, R-2 = 0.81 for dx = 1.1 vs. 0.8 mm) than with RB or UB (k = 0.04, R-2 = 0.03, and k = 0.07, R-2 = 0.07, respectively). Conclusion: Image-based full-field methods such as nu WERP enable cerebrovascular relative pressure mapping; however, accuracy is directly dependent on utilized spatial resolution.

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