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Record W4285342003 · doi:10.2196/34501

Augmented Reality in Vascular and Endovascular Surgery: Scoping Review

2022· article· en· W4285342003 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Serious Games · 2022
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAugmented realityVascular surgeryMedicineMEDLINESystematic reviewEndovascular surgeryMedical physicsComputer scienceRadiologySurgeryCardiac surgeryArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Technological advances have transformed vascular intervention in recent decades. In particular, improvements in imaging and data processing have allowed for the development of increasingly complex endovascular and hybrid interventions. Augmented reality (AR) is a subject of growing interest in surgery, with the potential to improve clinicians' understanding of 3D anatomy and aid in the processing of real-time information. This study hopes to elucidate the potential impact of AR technology in the rapidly evolving fields of vascular and endovascular surgery. OBJECTIVE: The aim of this review is to summarize the fundamental concepts of AR technologies and conduct a scoping review of the impact of AR and mixed reality in vascular and endovascular surgery. METHODS: A systematic search of MEDLINE, Scopus, and Embase was performed in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. All studies written in English from inception until January 8, 2021, were included in the search. Combinations of the following keywords were used in the systematic search string: ("augmented reality" OR "hololens" OR "image overlay" OR "daqri" OR "magic leap" OR "immersive reality" OR "extended reality" OR "mixed reality" OR "head mounted display") AND ("vascular surgery" OR "endovascular"). Studies were selected through a blinded process between 2 investigators (JE and AS) and assessed using data quality tools. RESULTS: AR technologies have had a number of applications in vascular and endovascular surgery. Most studies (22/32, 69%) used 3D imaging of computed tomography angiogram-derived images of vascular anatomy to augment clinicians' anatomical understanding during procedures. A wide range of AR technologies were used, with heads up fusion imaging and AR head-mounted displays being the most commonly applied clinically. AR applications included guiding open, robotic, and endovascular surgery while minimizing dissection, improving procedural times, and reducing radiation and contrast exposure. CONCLUSIONS: AR has shown promising developments in the field of vascular and endovascular surgery, with potential benefits to surgeons and patients alike. These include reductions in patient risk and operating times as well as in contrast and radiation exposure for radiological interventions. Further technological advances are required to overcome current limitations, including processing capacity and vascular deformation by instrumentation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score0.677

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.296
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it