- Poster presentation
- Open Access
Four dimensional analysis of aortic magnetic resonance images in connective tissue disorders: Novel indices of local and regional vessel properties
© Johnson et al; licensee BioMed Central Ltd. 2010
- Published: 21 January 2010
- Connective Tissue Disease
- Bicuspid Aortic Valve
- Left Ventricular Outflow Tract
- Connective Tissue Disorder
- Aortic Disease
Magnetic resonance (MR) imaging is a primary modality for following patients with connective tissue diseases, yet the amount image data precludes comprehensive analysis.
The goal of this study was to develop an automated 4D analysis method and demonstrate novel data presentation and parameters with prognostic potential.
MR scans of the thoracic aorta were acquired over 3 years on controls (Ctrl; n = 32) and patients with connective tissue disease (Pt; n = 37). Images were obtained at 1.5 T using a True FISP sequence. Imaging planes included left ventricular outflow tract and aortic arch views. 4D data from the two views were merged and a graph theory-based segmentation algorithm was applied to quantitate cross sectional area (CSA) and novel parameters for the entire length of aorta throughout the cardiac cycle.
The automated analysis method allowed for rapid and reliable quantitative 4D assessment of the entire aorta. This technique should prove useful not only for routine patient management but also for investigative evaluation of novel parameters that may predict aortic disease progression.
This article is published under license to BioMed Central Ltd.