Evidence map›Paper›PMID 35515717›Full record

ArticleBMJ simulation & technology enhanced learning2021

Use of three-dimensional printing for simulation in ultrasound education: a scoping review.

Patrick Gallagher, Ryan Smith, Gillian Sheppard

Abstract readScoping Review
In one paragraph

Article in BMJ simulation & technology enhanced learning, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Systematic Review of 3D-Printed Ultrasound-able Models in Graduate Medical Education.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2025
    Pooled it
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

3 authors.

Patrick GallagherFaculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada.
Ryan SmithFaculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada.
Gillian SheppardFaculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There is a significant learning curve when teaching ultrasonography to medical trainees; task trainers can help learners to bridge this gap and develop their skills. Three-dimensional printing technology has the potential to be a great tool in the development of such simulators. Objective: This scoping review aimed to identify what 3D-printed models have been used in ultrasound education to date, how they were created and the pros and limitations involved. Design: Researchers searched three online databases to identify 3D-printed ultrasound models used in medical education. Results: Twelve suitable publications were identified for inclusion in this review. The models from included articles simulated largely low frequency and/or high stakes events, with many models simulating needle guidance procedures. Most models were created by using patient imaging data and a computer-aided design software to print structures directly or print casting molds. The benefits of 3D-printed educational trainers are their low cost, reproducibility, patient specificity and accuracy. The current limitations of this technology are upfront investments and a lack of optimisation of materials. Conclusions: The use of 3D-printed ultrasound task trainers is in its infancy, and more research is needed to determine whether or not this technology will benefit medical learners in the future.

Indexed as

EducationSimulation Based EducationTask Trainers And Clinical Skills CentersUltrasound

Identifiers

PMID35515717
PMCPMC8936891

What OpenQuestion holds

Textmetadata
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.