Evidence map›Paper›PMID 41798664›Full record

ArticleCureus2026

A Reliable Low-Cost Three-Dimensional (3D)-Printed Brachial Plexus Model for Enhanced Anatomical Learning.

Manuel Cevallos, Joshua J Meyer, Jackson Beeching, Jad Mazboudi

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Manuel CevallosSurgery, University of Arizona College of Medicine - Phoenix, Phoenix, USA.
Joshua J MeyerMedical Education, Creighton University School of Medicine, Phoenix, USA.
Jackson BeechingMedical Education, Creighton University School of Medicine, Phoenix, USA.
Jad MazboudiMedical Education, Creighton University School of Medicine, Phoenix, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The brachial plexus is a complex network of nerve branches with a three-dimensional (3D) distribution, which can make it difficult for students at any level to identify its structures. Spatial visualization skills are required, but two-dimensional images are not ideal to learn about this neurological network. Despite the availability of commercial models and digital tools, substantial upfront costs, including but not limited to annual subscription fees, can pose a challenge for most resource-limited institutions, thus hindering effective learning. This technical report proposes a practical and cost-effective solution. Researchers demonstrate how direct 3D scanning of cadaveric structures is used to create an affordable 3D-printed model that captures key anatomical details. The 3D brachial plexus model preserves the traditional structure (no variants), facilitating student learning and enabling use in the lab or at home. In a brief pilot study using a voluntary, anonymous survey with Likert-style questions (institutional review board (IRB)-approved), the model was tested with current physician assistant students who took the anatomy course; their feedback is discussed in the article. This model can enhance learning and help bridge the educational gap at low-resource universities. Researchers believe in the universality of education; for that reason, the 3D-printed brachial plexus model is available to any academic faculty interested in using and evaluating it in their anatomical courses.

Indexed as

3d-printed model3d-scanninganatomybrachial plexusmedical educationspatial visualization

Identifiers

PMID41798664
PMCPMC12961632

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.