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Abstract #2625

Fully Automatic Vessel Wall Contour Detection and Wall Thickness Assessment in Common Carotid and Descending Aorta

Shan Gao1, Ronald van't Klooster1, Anne Brandts2, Stijntje D. Roes2, Reza Alizadeh Dehnavi3, Albert de Roos2, Jos J.M. Westenberg1, and Rob J. van der Geest1

1Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands, 2Department of Radiology, Leiden University Medical Center, Leiden, Netherlands, 3Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands

Atherosclerosis is characterized by thickening of the arterial wall. To monitor disease progression and regression, vessel wall segmentation is required for wall thickness assessment. In this study, we developed a fully automatic method to detect the vessel wall boundaries and quantify the wall thickness for both the common carotid artery and the descending aorta in MR images. The results demonstrated that our method has good agreement with manual segmentation, excellent scan-rescan reproducibility and capability of detecting vessel wall thickening in hypertensive patients. Therefore, the presented method is promising for application in future cohort studies.

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