Evidence map›Paper›PMID 28192461›Full record

ArticlePloS one2017

Canine neuroanatomy: Development of a 3D reconstruction and interactive application for undergraduate veterinary education.

Hazel Raffan, Julien Guevar, Matthieu Poyade, Paul M Rea

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 16% of its field
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

7 citing papers in PubMed, 40 citations in OpenAlex.

  1. The Application of 3D Anatomy for Teaching Veterinary Clinical Neurology.Animals : an open access journal from MDPI · 2023
    Article
  2. Article
  3. Article
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  5. IVET, an Interactive Veterinary Education Tool.Journal of animal science · 2019
    Article
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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 at 2 institutions in 1 country.

Hazel RaffanLaboratory of Human Anatomy, Thomson Building, School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, United Kingdom.
Julien GuevarSchool of Veterinary Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom.
Matthieu PoyadeDigital Design Studio, Glasgow School of Art, Glasgow, United Kingdom.
Paul M ReaLaboratory of Human Anatomy, Thomson Building, School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, United Kingdom.
University of Glasgow · GBGlasgow School of Art · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current methods used to communicate and present the complex arrangement of vasculature related to the brain and spinal cord is limited in undergraduate veterinary neuroanatomy training. Traditionally it is taught with 2-dimensional (2D) diagrams, photographs and medical imaging scans which show a fixed viewpoint. 2D representations of 3-dimensional (3D) objects however lead to loss of spatial information, which can present problems when translating this to the patient. Computer-assisted learning packages with interactive 3D anatomical models have become established in medical training, yet equivalent resources are scarce in veterinary education. For this reason, we set out to develop a workflow methodology creating an interactive model depicting the vasculature of the canine brain that could be used in undergraduate education. Using MR images of a dog and several commonly available software programs, we set out to show how combining image editing, segmentation and surface generation, 3D modeling and texturing can result in the creation of a fully interactive application for veterinary training. In addition to clearly identifying a workflow methodology for the creation of this dataset, we have also demonstrated how an interactive tutorial and self-assessment tool can be incorporated into this. In conclusion, we present a workflow which has been successful in developing a 3D reconstruction of the canine brain and associated vasculature through segmentation, surface generation and post-processing of readily available medical imaging data. The reconstructed model was implemented into an interactive application for veterinary education that has been designed to target the problems associated with learning neuroanatomy, primarily the inability to visualise complex spatial arrangements from 2D resources. The lack of similar resources in this field suggests this workflow is original within a veterinary context. There is great potential to explore this method, and introduce a new dimension into veterinary education and training.

Indexed as

Models, AnatomicAnimalsBrainDogsEducation, VeterinaryImaging, Three-DimensionalMagnetic Resonance ImagingNeuroanatomyReproducibility of ResultsSoftwareTomography, X-Ray ComputedUniversities

Identifiers

PMID28192461
PMCPMC5305238
OpenAlexW2587497605

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.