Sequential arterial feeder targeting with microscope-based augmented reality and multimodal navigation for brain arteriovenous malformation resection: an integrated operative workflow in 158 cases
In brief
Navigation-guided surgery showed 97.5% initial obliteration across 158 brain arteriovenous malformations
In a single-surgeon series, 154 of 158 navigation-assisted resections had complete obliteration on initial angiography, and 93% of patients were functionally independent at a median 15-month follow-up. Surgery caused loss of independence in 3.1% and death in 1.3%; without a comparison group, the results show feasibility, not that navigation improves outcomes.
- Journal
- Neurosurgical focus (Q1)
- Published
- 1 November 2026
- Study design
- Unclassified
- Evidence level
- Level 5, Expert Opinion (CEBM 5)
- Authors
- Sahin Hanalioglu, Ari D Kappel, Ignacio Mesina-Estarron, Anil Can, Daniel Munger, Erickson Torio, et al.
- PMID
- 42967342
- DOI
- 10.3171/2026.8.FOCUS26466
Why clinicians should know about it
- Picked for Anatomy (top studies of the week, 8 November 2026): Maps arterial feeder courses for operative approach planning
Abstract
OBJECTIVE: Early proximal arterial control is an established principle of brain arteriovenous malformation (bAVM) microsurgery but remains difficult to execute when feeding arteries are deep, obscured, or not apparent at the cortical surface. Herein, the authors describe the longitudinal clinical implementation of a workflow using multimodal navigation and microscope-based augmented reality (AR) to identify and target arterial feeders before substantial nidal dissection in bAVM resections. METHODS: Case-specific multimodal datasets were assembled according to clinical relevance and availability from CTA, high-resolution structural MRI with thin-slice T2-weighted imaging, MRA, and 3D rotational DSA studies and were fused within standard clinical neuronavigation platforms. All angiographically identifiable arterial feeders were segmented along their surgically relevant courses, prioritized as operative targets, and incorporated into exposure and corridor planning. Targets were displayed intraoperatively using the available navigation configuration, including microscope-based AR as the technology evolved. Functional MRI (fMRI) and diffusion tensor imaging (DTI) were coregistered selectively to provide cortical and tractographic context. Consecutive navigation-assisted bAVM resections performed by a single neurosurgeon from 2013 to 2025 were analyzed. Outcomes included angiographic obliteration, perioperative morbidity, mortality, and modified Rankin Scale (mRS) score change relative to baseline. RESULTS: Of 192 bAVM resections performed during the study period, 158 consecutive navigation-assisted resections comprised the analytical cohort and included Spetzler-Martin (SM) grades I-V. Complete obliteration on initial angiography after microsurgery was observed in 97.5% of cases (154/158). At a median follow-up of 15 months, 93.0% of patients were functionally independent (mRS score 0-2). An increase in the mRS score relative to baseline occurred in 18.4% of patients, most commonly reflecting minor, nondisabling deficits with preserved independence. Loss of independence attributable to surgery occurred in 3.1% of patients, and the mortality rate was 1.3%. CONCLUSIONS: Multimodal navigation with microscope-based AR was implemented longitudinally to identify and target arterial feeders before substantial nidal dissection, with selective integration of fMRI and DTI providing cortical and tractographic context for lesions near eloquent anatomy. Across SM grade I-V bAVMs, the workflow was feasible and was associated with high rates of angiographic obliteration and functional independence. By translating preoperative angioarchitecture into a planned sequence of discrete intraoperative arterial targets within their structural and functional context, the featured workflow provides a structured framework for operative planning, execution, and teaching in feeder-directed bAVM microsurgery.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.