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. 2022 Dec;127(12):1333-1341.
doi: 10.1007/s11547-022-01567-5. Epub 2022 Oct 18.

Segmentation techniques of brain arteriovenous malformations for 3D visualization: a systematic review

Elisa Colombo  1 , Tim Fick  2 , Giuseppe Esposito  3 , Menno Germans  3 , Luca Regli  3 , Tristan van Doormaal  3
Affiliations

Segmentation techniques of brain arteriovenous malformations for 3D visualization: a systematic review

Elisa Colombo et al. Radiol Med. 2022 Dec.

Abstract

Background: Visualization, analysis and characterization of the angioarchitecture of a brain arteriovenous malformation (bAVM) present crucial steps for understanding and management of these complex lesions. Three-dimensional (3D) segmentation and 3D visualization of bAVMs play hereby a significant role. We performed a systematic review regarding currently available 3D segmentation and visualization techniques for bAVMs.

Methods: PubMed, Embase and Google Scholar were searched to identify studies reporting 3D segmentation techniques applied to bAVM characterization. Category of input scan, segmentation (automatic, semiautomatic, manual), time needed for segmentation and 3D visualization techniques were noted.

Results: Thirty-three studies were included. Thirteen (39%) used MRI as baseline imaging modality, 9 used DSA (27%), and 7 used CT (21%). Segmentation through automatic algorithms was used in 20 (61%), semiautomatic segmentation in 6 (18%), and manual segmentation in 7 (21%) studies. Median automatic segmentation time was 10 min (IQR 33), semiautomatic 25 min (IQR 73). Manual segmentation time was reported in only one study, with the mean of 5-10 min. Thirty-two (97%) studies used screens to visualize the 3D segmentations outcomes and 1 (3%) study utilized a heads-up display (HUD). Integration with mixed reality was used in 4 studies (12%).

Conclusions: A golden standard for 3D visualization of bAVMs does not exist. This review describes a tendency over time to base segmentation on algorithms trained with machine learning. Unsupervised fuzzy-based algorithms thereby stand out as potential preferred strategy. Continued efforts will be necessary to improve algorithms, integrate complete hemodynamic assessment and find innovative tools for tridimensional visualization.

Keywords: Augmented reality; Blood vessel delineation; Cerebral arteriovenous malformation; Cerebrovascular surgery; Segmentation.

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Conflict of interest statement

Tristan van Doormaal is Co-founder and CMO of Augmedit bv, an augmented reality company.

Figures

Fig. 1
Fig. 1
Summary of search strategy (PRISMA flow chart) for relevant studies
See this image and copyright information in PMC

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