Automated segmentation of blood-flow regions in large thoracic arteries using 3D-cine PC-MRI measurements

Purpose: Quantitative analysis of vascular blood-flow, acquired by phase-contrast MRI requires an accurate segmentation of the vessel lumen. In clinical practice, 2D-cine velocity-encoded slices are inspected, and mostly the blood-flow lumen is segmented manually. However, segmentation of time-resolved volumetric blood-flow measurements is a tedious and time-consuming task. Methods: We propose an automated segmentation of large thoracic arteries, solely based on the 3D-cine phase-contrast MRI (PC-MRI) blood-flow data. In contrast to previous work, we employ an active-surface model, which is fast and topologically stable. An active surface model requires an initial surface, approximating the desired segmentation. We introduce a novel method to generate this surface, based on a voxel-wise temporal maximum of the blood-flow speed intensities. The active surface model balances forces, based on the surface structure and image features derived from the blood-flow data. The segmentation results were validated using volunteer studies, including time-resolved 3D and 2D blood-flow data. The segmented surface was intersected with a velocity-encoded PC-MRI slice, resulting in a cross-sectional contour of the lumen. These cross-sections were compared to reference contours that were manually delineated on high-resolution 2D-cine slices. Results: We show that our automated approach closely approximates the manual blood-flow segmentations, with error distances on the order of the voxel size. The initial surface provides a close approximation of the desired luminal geometry. This improves the convergence time of the active surface, and facilitates parametrization. Conclusions: We present an active-surface approach to segment the vessel lumen, suitable for quantitative analysis of 3D-cine PC-MRI blood-flow data. As opposed to the variety of thresholding and level-set approaches, the active-surface model is topologically stable. We introduce a novel methodology to generate an initial approximate surface, and have inspected various ...