Mixed Reality in the Surgical Management of Brain Arteriovenous Malformations

Background: Brain Arteriovenous malformations (AVMs) pose significant challenges in neurosurgery and require detailed planning and execution. The aim of this study is to assess the utility of Mixed Reality (MxR), an integration of Virtual Reality (VR) and Augmented Reality (AR), in the surgical treatment of AVMs.

Methods: A retrospective review of ten patients with AVMs was conducted. Preoperative planning used 360VR models, and AR markers were employed intraoperatively for precise targeting of arterial feeders. Surgical duration, blood loss, and postoperative outcomes were analyzed and stratified by Spetzler–Martin (SM) and Supplementary Spetzler–Martin (Supp SM) grades. A complex AVM case was selected for illustration to demonstrate the application of MxR in surgical planning and execution.

Results: MxR technologies enabled a comprehensive 3D understanding of the AVMs' angioarchitecture and facilitated the identification of 21 arterial feeders, including challenging deep feeders. Facilitated during surgery by MxR, arterial feeders were quickly identified and disconnected. This contributed to the efficiency of the AVM resection. The mean surgery duration was 5 hours and 11 minutes, with a mean blood loss of 507.5 ml. Statistically significant variations in surgery duration and blood loss were observed based on both SM and Supp SM grades. Two patients experienced worsened postoperative deficits, highlighting the inherent risks of AVM surgeries. The discrepancy in hospital stays between ruptured and unruptured AVMs, especially in SM Grade 3, elucidates the impact of rupture status on recovery.

Conclusion: In the present study, we describe a novel paradigm employing MxR for the surgical intervention of AVMs. By employing 3D VR for preoperative planning and AR for intraoperative guidance, we achieved unparalleled precision and efficiency in targeting deep arterial feeders. The results are promising, but larger studies are required to further validate this approach.

Publication History

Article published online:
05 February 2024