Comprehensive sex-specific and age-dependent analysis of four-dimensional flow cardiovascular magnetic resonance assessed aortic blood flow-related parameters in normal subjects using single-vendor magnetic resonance systems and single-vendor software
Open Access
- 13 August 2024
- journal article
- research article
- Published by Elsevier in Journal of Cardiovascular Magnetic Resonance
- Vol. 26 (2) , 101083
Abstract
No abstract availableKeywords
Funding Information
- Nederlandse Hartstichting (CVON2017-08-RADAR)
This publication has 30 references indexed in Scilit:
- Machine learning for the automatic assessment of aortic rotational flow and wall shear stress from 4D flow cardiac magnetic resonance imagingEuropean Radiology, 2022
- Quantitative normal values of helical flow, flow jets and wall shear stress of healthy volunteers in the ascending aortaEuropean Radiology, 2022
- Type A Aortic Dissection—Experience Over 5 DecadesJACC, 2020
- Fully automated 3D aortic segmentation of 4D flow MRI for hemodynamic analysis using deep learningMagnetic Resonance in Medicine, 2020
- Impact of age, sex, and global function on normal aortic hemodynamicsMagnetic Resonance in Medicine, 2020
- Aortic 4D flow MRI in 2 minutes using compressed sensing, respiratory controlled adaptive k‐space reordering, and inline reconstructionMagnetic Resonance in Medicine, 2019
- Age‐related changes of shape and flow dynamics in healthy adult aortas: A 4D flow MRI studyJournal of Magnetic Resonance Imaging, 2018
- Three‐dimensional quantification of vorticity and helicity from 3D cine PC‐MRI using finite‐element interpolationsMagnetic Resonance in Medicine, 2017
- Distribution, Determinants, and Normal Reference Values of Thoracic and Abdominal Aortic Diameters by Computed Tomography (from the Framingham Heart Study)The American Journal of Cardiology, 2013
- Quantitative 2D and 3D phase contrast MRI: Optimized analysis of blood flow and vessel wall parametersMagnetic Resonance in Medicine, 2008