Evidence map›Paper›PMID 41409853›Full record

ArticleSurgical neurology international2025

Augmented reality and 3D modeling for preoperative planning in microsurgical resection of brain arteriovenous malformations: A proof-of-concept study.

Anton Konovalov, Anastasia Kirichenko, Dmitri Okishev, Anton Artemyev, Anna Bogomazova, Marina Stogneva, Sofia Sergeeva, Ivan Erokhin, Yuri Pilipenko, Fyodor Grebenev and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Surgical neurology international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Anton KonovalovDepartment of Vascular Neurosurgery, N. N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russian Federation.
Anastasia KirichenkoFaculty of Medicine, Federal State Educational Institution of Higher Professional Education Lomonosov Moscow State University, Moscow, Russian Federation.
Dmitri OkishevDepartment of Vascular Neurosurgery, N. N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russian Federation.
Anton ArtemyevDepartment of Vascular Neurosurgery, N. N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russian Federation.
Anna BogomazovaInstitute for Bionic Technologies and Engineering, I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation.
Marina StognevaInstitute for Bionic Technologies and Engineering, I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation.
Sofia SergeevaInstitute for Bionic Technologies and Engineering, I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation.
Ivan ErokhinInstitute for Bionic Technologies and Engineering, I.M. Sechenov First Moscow State Medical University, Moscow, Russian Federation.
Yuri PilipenkoDepartment of Vascular Neurosurgery, N. N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russian Federation.
Fyodor GrebenevDepartment of Vascular Neurosurgery, N. N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russian Federation.
Shalva EliavaDepartment of Vascular Neurosurgery, N. N. Burdenko National Medical Research Center of Neurosurgery, Moscow, Russian Federation.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Brain arteriovenous malformations (AVMs) present significant surgical challenges due to their complex angioarchitecture. This study evaluates the clinical application of augmented reality (AR) and 3D modeling for preoperative planning in AVM microsurgery. Methods: A prospective series of 20 patients with Spetzler-Martin grade II-IV AVMs underwent preoperative 3D planning using computed tomography/magnetic resonance imaging segmentation (Inobitec DICOM Viewer Pro), AR navigation (Microsoft HoloLens 2 with Medgital software), and QR-code registration. Technical parameters including target registration error (TRE), preoperative preparation time, and intraoperative outcomes were analyzed. Results: Complete AVM resection was achieved in all cases (100%). The AR system demonstrated submillimeter accuracy (TRE: 0.5 ± 0.3 cm with QR-code vs. 1.2 ± 0.5 cm with craniometric points). Preoperative modeling required 15.3 ± 5.1 min, while AR navigation averaged 12.7 ± 3.2 min. Conclusion: Our findings support the feasibility of AR-assisted 3D planning as an adjunctive tool for AVM microsurgery. This proof-of-concept study suggests that AR technology may improve spatial orientation and facilitate surgical workflow, especially for complex lesions near eloquent areas. While the clinical benefit in terms of outcomes remains to be confirmed in larger prospective studies, the presented experience demonstrates technical reliability and practical applicability. Future integration with automated segmentation and cloud-based platforms may further enhance its clinical utility.

Indexed as

3D modelingArteriovenous malformationAugmented realityNeurosurgical navigationPreoperative planning

Identifiers

PMID41409853
PMCPMC12707730

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.