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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