Title

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

Share

COinS