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Erschienen in: Magnetic Resonance Materials in Physics, Biology and Medicine 6/2019

22.06.2019 | Research Article

Automatic correction of background phase offset in 4D-flow of great vessels and of the heart in MRI using a third-order surface model

verfasst von: Damian Craiem, Ariel F. Pascaner, Mariano E. Casciaro, Umit Gencer, Joaquin Alcibar, Gilles Soulat, Elie Mousseaux

Erschienen in: Magnetic Resonance Materials in Physics, Biology and Medicine | Ausgabe 6/2019

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Abstract

Objective

To evaluate an automatic correction method for velocity offset errors in cardiac 4D-flow acquisitions.

Materials and methods

Velocity offset correction was done in a plane-by-plane scheme and compared to a volumetric approach. Stationary regions were automatically detected. In vitro experiments were conducted in a phantom using two orientations and two encoding velocities (Venc). First- to third-order models were fit to the time-averaged images of the three velocity components. In vivo experiments included realistic ROIs in a volunteer superimposed to a phantom. In 15 volunteers, blood flow volume of the proximal and distal descending aorta, of the pulmonary artery (Qp) and the ascending aorta (Qs) was compared.

Results

Offset errors were reduced after correction with a third-order model, yielding residual phantom velocities below 0.6 cm/s and 0.4% of Venc. The plane-by-plane correction method was more effective than the volumetric approach. Mean velocities through superimposed ROIs of a volunteer vs phantom were highly correlated (r2 = 0.96). The significant difference between proximal and distal descending aortic flows was decreased after correction from 8.1 to − 1.4 ml (p < 0.001) and Qp/Qs reduced from 1.08 ± 0.09 to 1.01 ± 0.05.

Discussion

An automatic third-order model corrected velocity offset errors in 4D-flow acquisitions, achieving acceptable levels for clinical applications.
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Metadaten
Titel
Automatic correction of background phase offset in 4D-flow of great vessels and of the heart in MRI using a third-order surface model
verfasst von
Damian Craiem
Ariel F. Pascaner
Mariano E. Casciaro
Umit Gencer
Joaquin Alcibar
Gilles Soulat
Elie Mousseaux
Publikationsdatum
22.06.2019
Verlag
Springer International Publishing
Erschienen in
Magnetic Resonance Materials in Physics, Biology and Medicine / Ausgabe 6/2019
Print ISSN: 0968-5243
Elektronische ISSN: 1352-8661
DOI
https://doi.org/10.1007/s10334-019-00765-z

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