Three-dimensional segmentation and symbolic representation of cerebral vessels on 3DRA images of arteriovenous malformations. (December 2019)

• Record Type: Journal Article
• Authors: Chenoune, Y.; Tankyevych, O.; Li, F.; Piotin, M.; Blanc, R.; Petit, E.
• Is Part Of: Computers in biology and medicine. Volume 115(2019)
• Publication Date: 2019-12
• Subjects: 3D vascular segmentation -- Symbolic representation -- 3DRA -- Interventional planning -- Cerebral arteriovenous malformation -- Vascular network; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2019.103489
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Background: Endovascular embolization is a minimally invasive interventional method for the treatment of neurovascular pathologies such as aneurysms, arterial stenosis or arteriovenous malformations (AVMs). In this context, neuroradiologists need efficient tools for interventional planning and microcatheter embolization procedures optimization. Thus, the development of helpful methods is necessary to solve this challenging issue. Methods: A complete pipeline aiming to assist neuroradiologists in the visualization, interpretation and exploitation of three-dimensional rotational angiographic (3DRA) images for interventions planning in case of AVM is proposed. The developed method consists of two steps. First, an automated 3D region-based segmentation of the cerebral vessels which feed and drain the AVM is performed. From this, a graph-like tree representation of these connected vessels is then built. This symbolic representation provides a vascular network modelization with hierarchical and geometrical features that helps in the understanding of the complex angioarchitecture of the AVM. Results: The developed workflow achieves the segmentation of the vessels and of the malformation. It improves the 3D visualization of this complex network and highlights its three main components that are the arteries, the veins and the nidus. The symbolic representation then brings a better comprehension of the vessels angioarchitecture. It provides decomposition into topologically related vessels, offering the possibility to reduce the complexity due to the malformed vessels and also determine the optimal paths for AVM embolization during interventions planning. Conclusions: A relevant vascular network modelization has been developed that constitutes a breakthrough in the assistance of neuroradiologists for AVM endovascular embolization planning. Graphical abstract: Image 1 Highlights: An innovative process for endovascular therapy interventions planning. A complete pipeline including 3D segmentation and modelization of brain vessels. Modelization of the complex vascular network in case of AVMs from 3DRA images. Accurate 3D visualization distinguishing nidus, feeding arteries and draining veins. Interactively selecting a single vessel and defining the embolization paths.