Carotid Vessel Wall Segmentation Challenge

MICCAI endorsed event

Atherosclerosis, a leading cause of death worldwide, is a systemic disease that leads to plaque formation or luminal narrowing in multiple vascular beds, including carotid arteries. Atherosclerosis develops in the walls of the artery (vessel wall) and therefore it is important to measure the thickness of the vessel wall to differentiate normal and diseased vessels. Vessel wall (VW) magnetic resonance imaging (MRI), using black blood imaging, has been effective at visualizing normal and diseased arteries and characterizing atherosclerotic lesions. VW MRI has previously been used in research settings, with careful and comprehensive manual segmentation of the vessel wall. However, manual segmentation is labor intensive and requires a high degree of training in vessel wall review. On the other hand, automatic segmentation is also challenging for complex atherosclerotic lesions and in complex arterial geometries.

Vessel wall imaging (VWI) with MRI of the carotid artery has been recognized to be able to identify atherosclerotic lesions which pose increased risk of causing clinical events. However, traditional axial acquisition MRI sequences require a long scan. To ensure patient compliance and diagnostic image quality, a fast 3D carotid black blood MRI sequence (3D Motion Sensitized Driven Equilibrium prepared Rapid Gradient Echo, 3D-MERGE) has been developed, which allows large coverage of carotid arteries with submillimeter isotropic resolution in coronal acquisition, and is able to depict atherosclerotic lesion burden, severity, and luminal stenosis. This rapid sequence, which can complete a carotid scan in 2 minutes, has potential clinical application in identifying patients with advanced lesions but its application is limited due to the complexity of 3D image review, the large number of images available, and the lack of trained radiologists with extensive experience in the evaluation of carotid vessel
wall thickness.

In this challenge, the task is to segment the vessel wall from 3D-MERGE image with high accuracy and robustness. While the challenges of segmentation in different body regions are different, all vessel wall segmentation requires the basic steps of identifying the artery (localization) and lumen and outer wall segmentation. Then the wall thickness (difference between the lumen and outer wall contours) can be measured. Other clinically usable measurements such as lumen area or percent stenosis can also be derived from the vessel wall segmentation. Therefore, this challenge focuses on the important first step of vessel wall segmentation.