- Poster presentation
- Open Access
Motion correction using hierarchical local affine registration improves image quality and myocardial scar characterisation from T1 maps acquired with MOLLI
© Rault et al; licensee BioMed Central Ltd. 2013
- Published: 30 January 2013
- Motion Correction
- Improve Image Quality
- Chronic Myocardial Infarction
- Quality Score Assessment
- Signal Intensity Peak
T1 mapping enables true quantitative assessment of myocardial tissue, separating scars and healthy myocardium. The modified Look-Locker inversion recovery (MOLLI) sequence acquires eleven images over the duration of a minimum of fifteen heart beats to obtain the final T1 map, which is susceptible to undesired respiratory motion due to a relatively long breath-hold. We aimed to implement a motion correction method using a hierarchical local affine registration of MOLLI images and tested if it improved image quality and thus produced more accurate post contrast myocardial tissue T1 estimation.
Motion correction was implemented on T1 mapping images acquired 20 minutes post gadolinium contrast injection in 15 patients with a previous history of chronic myocardial infarction. Three experiments were carried out to compare the pre- and post-motion correction images. 1) Comparing visual quality score assessment of the T1 maps by two experienced independent observers; 2) comparing histogram distributions of voxel T1 values within the myocardium to allow tissue characterisation between the scarred region and the non-infarct region; and 3) comparing the "error of mismatch" measured by voxel misalignment in LV endocardial and epicardial borders. Wilcoxon signed rank test was performed to test for significant differences between the median errors of mismatch between the pre and post motion correction images.
Motion correction using hierarchical local affine registration yields better imaging quality thus allowing more accurate tissue characterization from T1 maps acquired with MOLLI sequence.
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.