An approach to the symbolic representation of brain arteriovenous malformations for management and treatment planning

4D Flat Panel Conebeam CTA for Analysis of the Angioarchitecture of Cerebral AVMs with a Novel Software Prototype

BACKGROUND AND PURPOSE

Time-resolved 3DRA (4D-DSA) and flat panel conebeam CTA are new methods for visualizing the microangioarchitecture of cerebral AVMs. We applied a 4D software prototype to a series of cases of AVMs to assess the utility of this method in relation to treatment planning.

MATERIALS AND METHODS

In 33 patients with AVMs, 4D volumes and flat panel conebeam CTA images were recalculated from existing 3D rotational angiography data. The multiplanar reconstructions were used to determine intranidal arteriovenous branching patterns, categorize them according to common classifications of AVM angioarchitecture, and compare the results with those from 2D-DSA.

RESULTS

4D flat panel conebeam CTA showed angioarchitectural features equal to or better than those of 2D-DSA in 30 of 33 cases. In particular, the reconstructions helped in understanding the intranidal microvasculature. Fistulous direct arteriovenous connections with a low degree of arterial branching (n = 22) could be distinguished from plexiform arterial networks before the transition to draining veins (n = 11). We identified AVMs with a single draining vein (n = 20) or multiple draining veins (n = 10). Arteriovenous shunts in the lateral wall of the draining veins (n = 22) could be distinguished from cases with increased venous branching and shunts between corresponding intranidal arteries and veins (n = 11). Limitations were the time-consuming postprocessing and the difficulties in correctly tracing intranidal vessels in larger and complex AVMs.

CONCLUSIONS

4D flat panel conebeam CTA reconstructions allow detailed analysis of the nidal angioarchitecture of AVMs. However, further improvements in temporal resolution and automated reconstruction techniques are needed to use the method generally in clinical practice.

Recent progress understanding pathophysiology and genesis of brain AVM-a narrative review

Considerable progress has been made over the past years to better understand the genetic nature and pathophysiology of brain AVM. For the actual review, a PubMed search was carried out regarding the embryology, inflammation, advanced imaging, and fluid dynamical modeling of brain AVM. Whole-genome sequencing clarified the genetic origin of sporadic and familial AVM to a large degree, although some open questions remain. Advanced MRI and DSA techniques allow for better segmentation of feeding arteries, nidus, and draining veins, as well as the deduction of hemodynamic parameters such as flow and pressure in the individual AVM compartments. Nonetheless, complete modeling of the intranidal flow structure by computed fluid dynamics (CFD) is not possible so far. Substantial progress has been made towards understanding the embryology of brain AVM. In contrast to arterial aneurysms, complete modeling of the intranidal flow and a thorough understanding of the mechanical properties of the AVM nidus are still lacking at the present time.

Three-dimensional segmentation and symbolic representation of cerebral vessels on 3DRA images of arteriovenous malformations

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.

Symbolic representation of brain vascular network with Arteriovenous Malformations from 3DRA images

Vascular imaging is crucial in the treatment of many diseases. In the case of cerebral ArterioVenous Malformation (AVM), where the vascular network can be deeply altered, an accurate knowledge of its topology is required. For this purpose, after a vessels segmentation and skeletization applied on 3D rotational angiographic images (3DRA), we build a symbolic tree representation of the vascular network thanks to topological descriptors, such as end points, junctions and branches. This leads to an efficient tool to assist the neuroradiologist to understand the feeding and the draining of the AVM and to apprehend its complex architecture in order to determine the best therapeutic strategy before and during embolization interventions.