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J Magn Reson Imaging. 2016 Feb;43(2):352-63. doi: 10.1002/jmri.24991. Epub 2015 Jun 30.

Use of multi-velocity encoding 4D flow MRI to improve quantification of flow patterns in the aorta.

Author information

1
Sydney Translational Imaging Laboratory, Sydney Medical School & Charles Perkins Centre, University of Sydney, Sydney, Australia.
2
Heart Research Institute, Newtown, Sydney, Australia.
3
Department of Cardiology, Royal North Shore Hospital, Sydney, Australia.
4
North Shore Heart Research Group, Kolling Institute, University of Sydney, Australia.
5
The Baird Institute, Camperdown, Australia.
6
Cardiothoracic Surgical Unit, Royal Prince Alfred Hospital, Sydney, Australia.
7
Department of Cardiology, Royal Prince Alfred Hospital, Sydney, Australia.
8
Department of Radiology, Royal Prince Alfred Hospital, Sydney, Australia.

Abstract

PURPOSE:

To show that the use of a multi-velocity encoding (VENC) 4D-flow approach offers significant improvements in the characterization of complex flow in the aorta. Four-dimensional flow magnetic resonance imaging (MRI) (4D-flow) can be used to measure complex flow patterns and dynamics in the heart and major vessels. The quality of the information derived from these measures is dependent on the accuracy of the vector field, which is limited by the vector-to-noise ratio.

MATERIALS AND METHODS:

A 4D-flow protocol involving three different VENC values of 150, 60, and 20 cm/s was performed on six control subjects and nine patients with type-B chronic aortic dissection at 3T MRI. Data were processed using a single VENC value (150 cm/s) or using a fused dataset that selected the lowest appropriate VENC for each voxel. Performance was analyzed by measuring spatial vector angular correlation, magnitude correlation, temporal vector conservation, and "real-world" streamline tracing performance.

RESULTS:

The multi-VENC approach provided a 31% improvement in spatial and 53% improvement in temporal precision of velocity vector measurements during the mid-late diastolic period, where 99% of the flow vectors in the normal aorta are below 20 cm/s. In low-flow conditions this resulted in practical improvements of greater than 50% in pathline tracking and streamline tracing quantified by streamline curvature measurements.

CONCLUSION:

A multi-VENC 4D-flow approach provides accurate vector data across normal physiological velocities observed in the aorta, dramatically improving outputs such as pathline tracking, streamline estimation, and further advanced analyses.

KEYWORDS:

4D-flow imaging; cardiovascular magnetic resonance; flow measurement; magnetic resonance imaging

PMID:
26130421
DOI:
10.1002/jmri.24991
[Indexed for MEDLINE]

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