"Fully automated tool to identify the aorta and compute flow using phas" by Akshay Goel, Roderick McColl et al.
 

Fully automated tool to identify the aorta and compute flow using phase-contrast MRI: validation and application in a large population based study

Document Type

Article

Abstract

PURPOSE: To assess if fully automated localization of the aorta can be achieved using phase contrast (PC) MR images. MATERIALS AND METHODS: 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. RESULTS: 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). CONCLUSION: 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.

Medical Subject Headings

Algorithms; Aorta (anatomy & histology, physiology); Aortography (methods); Blood Flow Velocity (physiology); Blood Volume (physiology); Blood Volume Determination (methods); Cardiac-Gated Imaging Techniques (methods); Female; Humans; Image Enhancement (methods); Image Interpretation, Computer-Assisted (methods, standards); Magnetic Resonance Angiography (methods); Male; Middle Aged; Reproducibility of Results; Sensitivity and Specificity; Software (standards); Software Validation

Publication Date

7-1-2014

Publication Title

Journal of magnetic resonance imaging : JMRI

E-ISSN

1522-2586

Volume

40

Issue

1

First Page

221

Last Page

8

PubMed ID

24115597

Digital Object Identifier (DOI)

10.1002/jmri.24338

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