Paper
13 March 2006 Patient-specific models of wall stress in abdominal aortic aneurysm: a comparison between MR and CT
Sander de Putter, Marcel Breeuwer, Frans N. van de Vosse, Ursula Kose, Frans A. Gerritsen
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Abstract
Finite element method based patient-specific wall stress in abdominal aortic aneurysm (AAA) may provide a more accurate rupture risk predictor than the currently used maximum transverse diameter. In this study, we have investigated the sensitivity of the wall stress in AAA with respect to geometrical variations. We have acquired MR and CT images for four patients with AAA. Three individual users have delineated the AAA vessel wall contours on the image slices. These contours were used to generate synthetic feature images for a deformable model based segmentation method. We investigated the reproducibility and the influence of the user variability on the wall stress. For sufficiently smooth models of the AAA wall, the peak wall stress is reproducible for three out of the four AAA geometries. The 0.99 percentiles of the wall stress show excellent reproducibility for all four AAAs. The variations induced by user variability are larger than the errors caused by the segmentation variability. The influence of the user variability appears to be similar for MR and CT. We conclude that the peak wall stress in AAA is sensitive to small geometrical variations. To increase reproducibility it appears to be best not to allow too much geometrical detail in the simulations. This could be achieved either by using a sufficiently smooth geometry representation or by using a more robust statistical parameter derived from the wall stress distribution.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sander de Putter, Marcel Breeuwer, Frans N. van de Vosse, Ursula Kose, and Frans A. Gerritsen "Patient-specific models of wall stress in abdominal aortic aneurysm: a comparison between MR and CT", Proc. SPIE 6143, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images, 61430D (13 March 2006); https://doi.org/10.1117/12.651675
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Cited by 2 scholarly publications.
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KEYWORDS
Image segmentation

Magnetic resonance imaging

Computed tomography

Modeling

Image resolution

Medical imaging

Arteries

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