Dependence of image quality of late gadolinium enhancement MRI of left atrium on number of patients imaged: results of multi-center trial DECAAF
https://doi.org/10.1186/1532-429X-16-S1-P146
© Vijayakumar et al.; licensee BioMed Central Ltd. 2014
Published: 16 January 2014
Keywords
Background
High-resolution late gadolinium enhancement (LGE) MRI is used to assess fibrosis of the left atrium (LA) and visualize post-ablation scar in patients with atrial fibrillation (AF). Only few centers with advanced expertise in cardiac MR (CMR) have shown successful and good quality LGE-MRI of the LA. In this work, we assess the dependence of image quality of LGE images on the number of patients imaged in the centers participating in the multi-center trial DECAAF (Delayed Enhancement - MRI determinant of successful Catheter Ablation of Atrial Fibrillation). Also, main causes of poor image quality were determined.
Methods
Fifteen centers with different degrees of CMR expertise and typical MRI hardware participated in DECAAF. Customized sequences for LGE of LA were installed on 17 Siemens scanners in participating centers. Nine centers used 1.5T scanners, five used 3T scanners and one used both 1.5 and 3T scanners. Three hundred and twenty nine AF patients underwent LGE-MRI prior to ablation to estimate the extent of LA fibrosis. One center (8 patients) was excluded from analysis because of two-years of prior experience in LGE-MRI of LA. Two independent readers assessed the image quality as 1- poor, 2 - fair or 3 - good. Poor quality images (57 patients, 17.3%) were analyzed to identify the causes for scan failure.
Results
Dependence of image quality of LGE-MRI on number of patients imaged.
Conclusions
The analysis of data from multi-center study DECAAF clearly shows a learning curve associated with LGE MRI of LA - imaging more patients improves image quality. Better training of MRI technologists may also further improve image quality.
Funding
This study was supported by the CARMA Center at the University of Utah.
Authors’ Affiliations
Copyright
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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.