Evidence map›Paper›PMID 41527637›Full record

ArticleCureus2025

Development of an Anatomically Accurate Three-Dimensional-Printed Spine Model From Computed Tomography Data Using Dual-Material Printing for Teaching and Visualization.

Stefan Tserovski, Todor G Bogdanov, Dimo A Yankov, Vlayko Vodenicharov, Dilyan Ferdinandov

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Stefan TserovskiOrthopedics and Traumatology, Medical University of Sofia, Sofia, BGR.
Todor G BogdanovMedical Physics, Medical University of Sofia, Sofia, BGR.
Dimo A YankovClinic of Neurosurgery, St. Ivan Rilski University Hospital, Sofia, BGR.
Vlayko VodenicharovGeneral Practice, Medical University of Sofia, Sofia, BGR.
Dilyan FerdinandovClinic of Neurosurgery, St. Ivan Rilski University Hospital, Sofia, BGR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate anatomical models play a crucial role in medical education by enhancing the understanding of complex spinal structures beyond traditional two-dimensional imaging and cadaveric preparations, which often present limitations in availability and durability. This technical report presents the development of a life-sized, anatomically accurate, three-dimensional-printed spine model derived from computed tomography data. The imaging data were processed and segmented to isolate vertebrae and intervertebral discs, after which refined stereolithography files were generated. The vertebral structures were printed using polylactic acid filament to replicate bone rigidity, while the intervertebral discs were fabricated from thermoplastic polyurethane to simulate their flexibility. The final model preserved precise anatomical proportions, vertebral morphology, and spatial relationships, allowing realistic manipulation and functional visualization of spinal segments. The result is a cost-effective and durable educational tool suitable for teaching, demonstration, and anatomical visualization in medical training. This approach establishes a reproducible workflow for creating high-fidelity, patient-specific models and provides a foundation for future developments, such as incorporating soft tissues or pathological variations.

Indexed as

anatomical spine modelanatomical visualizationdual-material fabricationmedical educationthree-dimensional printing

Identifiers

PMID41527637
PMCPMC12790608

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.