The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Augmented reality in neurosurgery: a systematic review
Open accessAbstract
Neuronavigation has become an essential neurosurgical tool in pursuing minimal invasiveness and maximal safety, even though it has several technical limitations. Augmented reality (AR) neuronavigation is a significant advance, providing a real-time updated 3D virtual model of anatomical details, overlaid on the real surgical field. Currently, only a few AR systems have been tested in a clinical setting. The aim is to review such devices. We performed a PubMed search of reports restricted to human studies of in vivo applications of AR in any neurosurgical procedure using the search terms “Augmented reality” and “Neurosurgery.” Eligibility assessment was performed independently by two reviewers in an unblinded standardized manner. The systems were qualitatively evaluated on the basis of the following: neurosurgical subspecialty of application, pathology of treated lesions and lesion locations, real data source, virtual data source, tracking modality, registration technique, visualization processing, display type, and perception location. Eighteen studies were included during the period 1996 to September 30, 2015. The AR systems were grouped by the real data source: microscope (8), hand- or head-held cameras (4), direct patient view (2), endoscope (1), and X-ray fluoroscopy (1) head-mounted display (1). A total of 195 lesions were treated: 75 (38.46 %) were neoplastic, 77 (39.48 %) neurovascular, and 1 (0.51 %) hydrocephalus, and 42 (21.53 %) were undetermined. Current literature confirms that AR is a reliable and versatile tool when performing minimally invasive approaches in a wide range of neurosurgical diseases, although prospective randomized studies are not yet available and technical improvements are needed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gotzsche, P. C., Ioannidis, J. P. A., Clarke, M., Devereaux, P. J., Kleijnen, J., & Moher, D. (2009) · BMJ · doi:10.1136/bmj.b2700 · Cited by 17,648
Cited by
Digital twin: values, challenges and enablers from a modeling perspective
Rasheed, A., San, O., & Kvamsdal, T. (2020) · IEEE Access · doi:10.1109/access.2020.2970143 · Cited by 1,952
Augmented Reality in Medicine: Systematic and Bibliographic Review
Eckert, M., Volmerg, J. S., & Friedrich, C. M. (2019) · JMIR mHealth and uHealth · doi:10.2196/10967 · Cited by 336
Digital Twin: Values, Challenges and Enablers
Rasheed, A., San, O., & Kvamsdal, T. (2019) · arXiv · doi:10.48550/arxiv.1910.01719 · Cited by 81
Ibrahim, Z., & Money, A. G. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103102 · Cited by 26
Metadata
- Authors
- Meola, A., Cutolo, F., Carbone, M., Cagnazzo, F., Ferrari, M., & Ferrari, V.
- Venue
- Neurosurgical Review
- Published
- 2016-05-07
- Volume
- 40
- Issue
- 4
- Pages
- 537-548
- ISSN
- 0344-5607 (ISSN-L)
- 1437-2320
- OpenAlex
- W2346369493
- Cited by
- 349
- References
- 1
- FWCI
- 6.44
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Augmented reality in neurosurgery: a systematic review. https://app.cochat.ai/papers/10.1007/s10143-016-0732-9
- The paper
- Meola, A., Cutolo, F., Carbone, M., Cagnazzo, F., Ferrari, M., & Ferrari, V. (2017). Augmented reality in neurosurgery: a systematic review. Neurosurgical Review. https://doi.org/10.1007/s10143-016-0732-9
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.