- Oral presentation
- Open Access
Efficient 3D late gadolinium enhancement imaging using the CLAWS respiratory motion control algorithm
© Keegan et al; licensee BioMed Central Ltd. 2013
- Published: 30 January 2013
- Cardiac Cycle
- Late Gadolinium Enhancement
- Image Quality Score
- Late Gadolinium Enhancement Imaging
- Acquisition Duration
Acquisition durations of navigator gated high resolution 3D late gadolinium enhancement (LGE) studies are long (1,2). While implementation of the continuously adaptive windowing strategy (CLAWS (3)) - which results in the fastest possible acquisition duration for a given breathing pattern and navigator acceptance window size - may be beneficial, the respiratory-dependent and therefore, non-smooth k-space acquisition order during gadolinium wash-out could result in increased image artifact. This study was performed to investigate if CLAWS could be used to increase the respiratory efficiency of 3D LGE imaging without detriment to image quality.
Whole-heart 3D (32-36 slices, 1.5 x 1.5 x 4 mm, reconstructed to 64-72 slices, 0.7 x 0.7x.2 mm) inversion-prepared segmented gradient echo imaging was performed in 18 consecutive patients on a Siemens 1.5 Tesla Avanto scanner. Two acquisitions were performed in random order, one with CLAWS respiratory motion control and one with an end-expiratory tracking accept/reject algorithm (EE-ARA). Imaging started 15 minutes post-gadolinium administration with inversion-time scouting both before and after each acquisition. Paired t-testing was used to compare the acquisition durations against the best possible scan times that could have been achieved for the patient-specific respiratory patterns which were determined from retrospective analysis of the navigator data stored with each acquisition. CLAWS and EE-ARA qualitative image quality scores (ranging from 1 = non-diagnostic to 5 = excellent) were compared using paired-Wilcoxon analysis.
We conclude that the CLAWS algorithm allows efficient acquisition of free-breathing 3D LGE without detriment to the image quality.
Wellcome Trust: WT093953MA; NIHR (National Institute for Health Research); British Heart Foundation Intermediate Clinical Research Fellowship.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.