Back to Search
Start Over
Fully automated tool to identify the aorta and compute flow using phase-contrast MRI: validation and application in a large population based study
- Source :
- Journal of magnetic resonance imaging : JMRI. 40(1)
- Publication Year :
- 2013
-
Abstract
- To assess if fully automated localization of the aorta can be achieved using phase contrast (PC) MR images.PC cardiac-gated MR images were obtained as part of a large population-based study. A fully automated process using the Hough transform was developed to localize the ascending aorta (AAo) and descending aorta (DAo). The study was designed to validate this technique by determining: (i) its performance in localizing the AAo and DAo; (ii) its accuracy in generating AAo flow volume and DAo flow volume; and (iii) its robustness on studies with pathological abnormalities or imaging artifacts.The algorithm was applied successfully on 1884 participants. In the randomly selected 50-study validation set, linear regression shows an excellent correlation between the automated (A) and manual (M) methods for AAo flow (r = 0.99) and DAo flow (r = 0.99). Bland-Altman difference analysis demonstrates strong agreement with minimal bias for: AAo flow (mean difference [A-M] = 0.47 ± 2.53 mL), and DAo flow (mean difference [A-M] = 1.74 ± 2.47 mL).A robust fully automated tool to localize the aorta and provide flow volume measurements on phase contrast MRI was validated on a large population-based study.
- Subjects :
- Male
Blood Volume
Blood Volume Determination
Software Validation
Cardiac-Gated Imaging Techniques
Reproducibility of Results
Middle Aged
Image Enhancement
Aortography
Sensitivity and Specificity
Article
Image Interpretation, Computer-Assisted
Humans
Female
Algorithms
Aorta
Blood Flow Velocity
Magnetic Resonance Angiography
Software
Subjects
Details
- ISSN :
- 15222586
- Volume :
- 40
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Journal of magnetic resonance imaging : JMRI
- Accession number :
- edsair.pmid..........b2c95dc5842d650e3f04f6e1b7ca4c7c