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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.
Insights
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.
Abstract:
Aortic stiffness has proven to be an important diagnostic and prognostic factor of many cardiovascular diseases, as well as an estimate of overall cardiovascular health. Pulse wave velocity (PWV) represents a good measure of the aortic stiffness, while the aortic distensibility is used as an aortic elasticity index. Obtaining the PWV and the aortic distensibility from magnetic resonance imaging (MRI) data requires diverse segmentation tasks, namely the extraction of the aortic center line and the segmentation of aortic regions, combined with signal processing methods for the analysis of the pulse wave. In our study non-contrasted MRI images of abdomen were used in healthy volunteers (22 data sets) for the sake of non-invasive analysis and contrasted magnetic resonance (MR) images were used for the aortic examination of Marfan syndrome patients (8 data sets). In this research we present a novel robust segmentation technique for the PWV and aortic distensibility calculation as a complete image processing toolbox. We introduce a novel graph-based method for the centerline extraction of a thoraco-abdominal aorta for the length calculation from 3-D MRI data, robust to artifacts and noise. Moreover, we design a new projection-based segmentation method for transverse aortic region delineation in cardiac magnetic resonance (CMR) images which is robust to high presence of artifacts. Finally, we propose a novel method for analysis of velocity curves in order to obtain pulse wave propagation times. In order to validate the proposed method we compare the obtained results with manually determined aortic centerlines and a region segmentation by an expert, while the results of the PWV measurement were compared to a validated software (LUMC, Leiden, the Netherlands). The obtained results show high correctness and effectiveness of our method for the aortic PWV and distensibility calculation.
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