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Updated: May 4, 2026

Pulse Wave Velocity Testing in the Baltimore Longitudinal Study of Aging
Published on: February 7, 2014
Robust segmentation methods with an application to aortic pulse wave velocity calculation
Danilo Babin1, Daniel Devos2, Aleksandra Pižurica1
1Department of Telecommunications and Information Processing - TELIN-IPI-iMinds, Faculty of Sciences, Ghent University, Sint-Pietersnieuwstraat 41, B-9000 Ghent, Belgium.
This study introduces a new image processing toolbox for calculating aortic stiffness using magnetic resonance imaging (MRI). The novel method accurately measures pulse wave velocity (PWV) and aortic distensibility, crucial for cardiovascular health assessment.
Area of Science:
- Cardiovascular imaging and analysis
- Medical image processing
- Biomedical engineering
Background:
- Aortic stiffness is a key indicator of cardiovascular disease and overall cardiovascular health.
- Pulse wave velocity (PWV) and aortic distensibility are vital measures of aortic stiffness and elasticity.
- Accurate measurement of PWV and distensibility from MRI requires robust segmentation and signal processing.
Purpose of the Study:
- To present a novel, robust image processing toolbox for calculating aortic stiffness (PWV and distensibility) from MRI data.
- To develop advanced segmentation techniques for accurate thoraco-abdominal aorta centerline extraction and transverse aortic region delineation.
- To introduce a new method for analyzing velocity curves to determine pulse wave propagation times.
Main Methods:
- A novel graph-based method for 3D thoraco-abdominal aorta centerline extraction from non-contrasted abdominal MRI.
- A new projection-based segmentation method for transverse aortic region delineation in cardiac MRI, robust to artifacts.
- A novel method for velocity curve analysis to obtain pulse wave propagation times.
- Validation against manual segmentations and a validated software for PWV measurement.
Main Results:
- The developed toolbox provides a complete solution for aortic PWV and distensibility calculation.
- The graph-based centerline extraction is robust to artifacts and noise.
- The projection-based segmentation effectively delineates aortic regions even with high artifact presence.
- Validation demonstrated high correctness and effectiveness of the proposed methods.
Conclusions:
- The novel image processing toolbox offers a correct and effective approach for calculating aortic PWV and distensibility from MRI.
- The developed segmentation techniques are robust and suitable for clinical application in cardiovascular assessment.
- This work advances non-invasive methods for evaluating aortic stiffness and cardiovascular health.
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