Evidence map›Paper›PMID 36296054›Full record

ArticleMicromachines2022

Enhanced Visualisation of Normal Anatomy with Potential Use of Augmented Reality Superimposed on Three-Dimensional Printed Models.

Jade Geerlings-Batt, Carley Tillett, Ashu Gupta, Zhonghua Sun

Abstract read
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

4 authors.

Jade Geerlings-BattDiscipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth, WA 6845, Australia.
Carley TillettCurtin HIVE (Hub for Immersive Visualisation and eResearch), Curtin University, Perth, WA 6845, Australia.ORCID 0000-0003-3854-8816
Ashu GuptaDepartment of Medical Imaging, Fiona Stanley Hospital, Perth, WA 6150, Australia.
Zhonghua SunDiscipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth, WA 6845, Australia.ORCID 0000-0002-7538-4761

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anatomical knowledge underpins the practice of many healthcare professions. While cadaveric specimens are generally used to demonstrate realistic anatomy, high cost, ethical considerations and limited accessibility can often impede their suitability for use as teaching tools. This study aimed to develop an alternative to traditional teaching methods; a novel teaching tool using augmented reality (AR) and three-dimensional (3D) printed models to accurately demonstrate normal ankle and foot anatomy. An open-source software (3D Slicer) was used to segment a high-resolution magnetic resonance imaging (MRI) dataset of a healthy volunteer ankle and produce virtual bone and musculature objects. Bone and musculature were segmented using seed-planting and interpolation functions, respectively. Virtual models were imported into Unity 3D, which was used to develop user interface and achieve interactability prior to export to the Microsoft HoloLens 2. Three life-size models of bony anatomy were printed in yellow polylactic acid and thermoplastic polyurethane, with another model printed in white Visijet SL Flex with a supporting base attached to its plantar aspect. Interactive user interface with functional toggle switches was developed. Object recognition did not function as intended, with adequate tracking and AR superimposition not achieved. The models accurately demonstrate bony foot and ankle anatomy in relation to the associated musculature. Although segmentation outcomes were sufficient, the process was highly time consuming, with effective object recognition tools relatively inaccessible. This may limit the reproducibility of augmented reality learning tools on a larger scale. Research is required to determine the extent to which this tool accurately demonstrates anatomy and ascertain whether use of this tool improves learning outcomes and is effective for teaching anatomy.

Indexed as

anatomyanatomy educationaugmented realityenhanced visualisationMicrosoft HoloLens 2simulationthree-dimensional printing

Identifiers

PMID36296054
PMCPMC9608320

What OpenQuestion holds

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LicenceCC BY
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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.