Focused navigation for respiratory–motion-corrected free-running radial 4D flow MRI

Mariana B.L. Falcão, Giulia M.C. Rossi, Tobias Rutz, Milan Prša, Estelle Tenisch, Liliana Ma, Elizabeth K. Weiss, Justin J. Baraboo, Jérôme Yerly, Michael Markl, Matthias Stuber, Christopher W. Roy*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Purpose: To validate a respiratory motion correction method called focused navigation (fNAV) for free-running radial whole-heart 4D flow MRI. Methods: Using fNAV, respiratory signals derived from radial readouts are converted into three orthogonal displacements, which are then used to correct respiratory motion in 4D flow datasets. Hundred 4D flow acquisitions were simulated with non-rigid respiratory motion and used for validation. The difference between generated and fNAV displacement coefficients was calculated. Vessel area and flow measurements from 4D flow reconstructions with (fNAV) and without (uncorrected) motion correction were compared to the motion-free ground-truth. In 25 patients, the same measurements were compared between fNAV 4D flow, 2D flow, navigator-gated Cartesian 4D flow, and uncorrected 4D flow datasets. Results: For simulated data, the average difference between generated and fNAV displacement coefficients was 0.04 (Formula presented.) 0.32 mm and 0.31 (Formula presented.) 0.35 mm in the x and y directions, respectively. In the z direction, this difference was region-dependent (0.02 (Formula presented.) 0.51 mm up to 5.85 (Formula presented.) 3.41 mm). For all measurements (vessel area, net volume, and peak flow), the average difference from ground truth was higher for uncorrected 4D flow datasets (0.32 (Formula presented.) 0.11 cm2, 11.1 (Formula presented.) 3.5 mL, and 22.3 (Formula presented.) 6.0 mL/s) than for fNAV 4D flow datasets (0.10 (Formula presented.) 0.03 cm2, 2.6 (Formula presented.) 0.7 mL, and 5.1 (Formula presented.).9 mL/s, p < 0.05). In vivo, average vessel area measurements were 4.92 (Formula presented.) 2.95 cm2, 5.06 (Formula presented.) 2.64 cm2, 4.87 (Formula presented.) 2.57 cm2, 4.87 (Formula presented.) 2.69 cm2, for 2D flow and fNAV, navigator-gated and uncorrected 4D flow datasets, respectively. In the ascending aorta, all 4D flow datasets except for the fNAV reconstruction had significantly different vessel area measurements from 2D flow. Overall, 2D flow datasets demonstrated the strongest correlation to fNAV 4D flow for both net volume (r2 = 0.92) and peak flow (r2 = 0.94), followed by navigator-gated 4D flow (r2 = 0.83 and r2 = 0.86, respectively), and uncorrected 4D flow (r2 = 0.69 and r2 = 0.86, respectively). Conclusion: fNAV corrected respiratory motion in vitro and in vivo, resulting in fNAV 4D flow measurements that are comparable to those derived from 2D flow and navigator-gated Cartesian 4D flow datasets, with improvements over those from uncorrected 4D flow.

Original languageEnglish (US)
Pages (from-to)117-132
Number of pages16
JournalMagnetic resonance in medicine
Issue number1
StatePublished - Jul 2023


  • 4D flow MRI
  • fNAV
  • focused navigation
  • free-running 3D radial PC-MRI
  • motion correction

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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