Evidence map›Paper›PMID 38717736›Full record

ArticleInternational journal of computer assisted radiology and surgery2024

Evaluation of augmented reality training for a navigation device used for CT-guided needle placement.

T Stauffer, Q Lohmeyer, S Melamed, A Uhde, R Hostettler, S Wetzel, M Meboldt

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Evaluation of a mixed reality navigation simulator for training of minimally invasive interventions of the spine: a pilot didactic plan.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Article
  2. A Mixed-Reality Navigation Simulator for Training Infiltration Procedures of the Spine: Evaluation in Kambin Triangle Location.The international journal of medical robotics + computer assisted surgery : MRCAS · 2026
    Article
  3. 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

7 authors.

T StaufferProduct Development Group Zurich, ETH Zurich, Leonhardstrasse 21, 8092, Zurich, Switzerland. tobiasta@ethz.ch.ORCID http://orcid.org/0009-0003-1878-8967
Q LohmeyerProduct Development Group Zurich, ETH Zurich, Leonhardstrasse 21, 8092, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-3802-5329
S MelamedMedical Templates AG, Technoparkstrasse 1, 8005, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-7018-9492
A UhdeMedical Templates AG, Technoparkstrasse 1, 8005, Zurich, Switzerland.
R HostettlerMedical Templates AG, Technoparkstrasse 1, 8005, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-6196-1153
S WetzelMedical Templates AG, Technoparkstrasse 1, 8005, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-0003-3609
M MeboldtProduct Development Group Zurich, ETH Zurich, Leonhardstrasse 21, 8092, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-5828-5406

Funding

Innosuisse - Schweizerische Agentur für Innovationsförderung 63540_1_INNO-LS
6 · The paper itself

Abstract

purposeNumerous navigation devices for percutaneous, CT-guided interventions exist and are, due to their advantages, increasingly integrated into the clinical workflow. However, effective training methods to ensure safe usage are still lacking. This study compares the potential of an augmented reality (AR) training application with conventional instructions for the Cube Navigation System (CNS), hypothesizing enhanced training with AR, leading to safer clinical usage.

methodsAn AR-tablet app was developed to train users puncturing with CNS. In a study, 34 medical students were divided into two groups: One trained with the AR-app, while the other used conventional instructions. After training, each participant executed 6 punctures on a phantom (204 in total) following a standardized protocol to identify and measure two potential CNS procedural user errors: (1) missing the coordinates specified and (2) altering the needle trajectory during puncture. Training performance based on train time and occurrence of procedural errors, as well as scores of User Experience Questionnaire (UEQ) for both groups, was compared.

resultsTraining duration was similar between the groups. However, the AR-trained participants showed a 55.1% reduced frequency of the first procedural error (p > 0.05) and a 35.1% reduced extent of the second procedural error (p < 0.01) compared to the conventionally trained participants. UEQ scores favored the AR-training in five of six categories (p < 0.05).

conclusionThe AR-app enhanced training performance and user experience over traditional methods. This suggests the potential of AR-training for navigation devices like the CNS, potentially increasing their safety, ultimately improving outcomes in percutaneous needle placements.

Indexed as

Augmented RealityNeedlesPhantoms, ImagingTomography, X-Ray ComputedAdultClinical CompetenceFemaleHumansMalePuncturesRadiography, InterventionalStudents, MedicalAugmented realityInterventional radiologyMedical educationUser study

Identifiers

PMID38717736
PMCPMC11607048

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.