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Session: Poster session 2 (Odd numbers)
Session starts: Friday 27 January, 10:00
Presentation starts: 10:00

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Floor Fasen (Eindhoven University of Technology, Catharina Hospital Eindhoven, Philips Research)
Daniek van Aarle (Eindhoven University of Technology, Philips Research)
Marc van Sambeek (Catharina Hospital Eindhoven)
Arjen van der Horst (Philips Research)
Richard Lopata (Eindhoven University of Technology)

Abstract:
An abdominal aortic aneurysm (AAA) is a localized widening of the abdominal aorta. AAA can lead to death because of rupture of the wall and therefore a clinical intervention is performed when the diameter of the aorta is too large. However, a better patient-specific marker is needed. The mean wall thickness is an indicator for rupture risk [1], which varies significantly within and between patients [2]. So far, regional thickness has not been used in previous rupture risk analysis studies, since it cannot be measured with CT, MRI and non-invasive ultrasound (US). In this study, a method using intravascular ultrasound (IVUS) is proposed. Four setups were used to acquire IVUS (Philips PV Visions 0.035) images of aortas. First, two poly(vinyl alcohol) phantoms were created with a given wall thickness. The phantoms were placed in a mock circulation set-up to mimic in vivo hemodynamic conditions. Second, seven static porcine aortas were imaged using IVUS and μCT, where the μCT images serve as ground truth. Third, 347 IVUS images of AAAs were simulated based on CTA images. Fourth, three AAA patients were imaged during surgical intervention. For the porcine aortas, two automatic segmentation methods were adopted, optimized and compared to segment the lumen and outer wall: a gradient-based and an active contours method. Finally, the geometry and wall thickness were obtained. The segmentation quality was investigated using the Hausdorff distance (HD) and the similarity index (SI). The segmentation quality of the inner wall (HD=0.9 mm, SI=0.96) is better than the outer wall (HD=1.3 mm, SI=0.95). The active contours method (HD=0.8 mm, SI=0.97) outperforms the gradient-based method (HD=1.4 mm, SI=0.94). In this study we showed that using IVUS, the geometry and wall thickness of the aorta can be obtained accurately. This method can be used to improve AAA rupture risk assessment in a minimally invasive manner. In future studies, the phantom, simulated and patient data will be explored using the developed conventional methods and a convolutional neural network. For large aneurysms, the wall is not always in the field of view. Hence, a combined intravascular-extravascular approach will be considered. [1] Di Martino, E. S., et al. Journal of Vascular Surgery (2006). [2] Raghavan, M. L., et al. Journal of biomechanics (2006).