Trial reportJournal of magnetic resonance imaging : JMRI2014
Fully automated tool to identify the aorta and compute flow using phase-contrast MRI: validation and application in a large population based study.
Trial report in Journal of magnetic resonance imaging : JMRI, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Automated Segmentation of Tissues Using CT and MRI: A Systematic Review.Academic radiology · 2019Pooled it
- Automated Quantification of Simple and Complex Aortic Flow Using 2D Phase Contrast MRI.Medicina (Kaunas, Lithuania) · 2024Article
- Fully-automated deep learning-based flow quantification of 2D CINE phase contrast MRI.European radiology · 2023Article
- Automated quantification of myocardial tissue characteristics from native TJournal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2020Article
- Automatic protocol for quantifying the vasoconstriction in blood vessel images.Biomedical optics express · 2020Article
- A new vessel segmentation algorithm for robust blood flow quantification from two-dimensional phase-contrast magnetic resonance images.Clinical physiology and functional imaging · 2019Article
- Quantification of aortic pulse wave velocity from a population based cohort: a fully automatic method.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2019Article
- Automated analysis of cardiovascular magnetic resonance myocardial native TJournal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2019Article
- Article
- Cardiac imaging: working towards fully-automated machine analysis & interpretation.Expert review of medical devices · 2017Review
- Challenges of cardiac image analysis in large-scale population-based studies.Current cardiology reports · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
purposeTo assess if fully automated localization of the aorta can be achieved using phase contrast (PC) MR images. MATERIALS AND
methodsPC 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.
resultsThe 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).
conclusionA 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.