- Poster presentation
- Open Access
Evaluation of the effect of myocardial localisation errors on myocardial blood flow estimates from DCE-MRI
© Biglands et al; licensee BioMed Central Ltd. 2010
- Published: 21 January 2010
- Myocardial Blood Flow
- Segmentation Algorithm
- Adenosine Stress
- Contour Error
- Deconvolution Algorithm
Dynamic contrast enhanced myocardial perfusion MRI (DCE-MRI) has the potential to be superior to other currently available imaging techniques for the assessment of myocardial ischaemia. Quantitative analysis of cardiac perfusion is currently not routinely carried out because of the time consuming process of manually segmenting the myocardium from large DCE-MRI datasets. A range of automated segmentation algorithms have been proposed which quote results in terms of distance error or estimated myocardial blood flow (MBF). However, the relationship between these two evaluation measures is not clear, making objective comparisons of algorithm performance difficult.
The purpose of this study was to investigate the effect of errors in the placement of endocardial and epicardial contours on estimated MBF in the analysis of DCE-MRI data.
Rest and adenosine stress DCE-MRI was carried out on 10 healthy volunteers. Manually segmented epicardial and endocardial contours were radially dilated and eroded by up to three voxels. The regions described by these contours were used to estimate mean MBFs by a Fermi-constrained deconvolution algorithm.
These results suggest that the current accuracy achievable by segmentation algorithms for the assessment of transmural perfusion is sufficient for MBF estimation and future work should focus on decreasing algorithm failure rates, rather than achieving marginal improvements in segmentation accuracy. The endocardium is the most critical contour and the inclusion of any blood pool voxels should be avoided.
This article is published under license to BioMed Central Ltd.