Evidence map›Paper›PMID 36830866›Full record

ArticleBiomedicines2023

Development of a 3D Printed Brain Model with Vasculature for Neurosurgical Procedure Visualisation and Training.

Manuel Encarnacion Ramirez, Issael Ramirez Pena, Rossi E Barrientos Castillo, Albert Sufianov, Evgeniy Goncharov, Jose A Soriano Sanchez, Manuel Colome-Hidalgo, Renat Nurmukhametov, José Rafael Cerda Céspedes, Nicola Montemurro

Abstract read
In one paragraph

Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. The Application Value of Personalized 3D Printed Navigation Molds in Neurosurgery.Journal of neurological surgery. Part A, Central European neurosurgery · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. 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

10 authors.

Manuel Encarnacion RamirezDepartment of Neurosurgery, RUDN University, 121359 Moscow, Russia.ORCID 0000-0003-3541-0635
Issael Ramirez PenaThe Royal Melbourne Hospital, Melbourne, VIC 3000, Australia.
Rossi E Barrientos CastilloDepartment of Neurosurgery, RUDN University, 121359 Moscow, Russia.ORCID 0000-0001-5332-6811
Albert SufianovDepartment of Neurosurgery, First Moscow State Medical University (Sechenov University), 121359 Moscow, Russia.
Evgeniy GoncharovTraumatology and Orthopedics Center, Central Clinical Hospital of the Russian Academy of Sciences, 121359 Moscow, Russia.
Jose A Soriano SanchezInstituto Soriano de Cirugía de Columna Mínimamente Invasiva at ABC Hospital, Neurological Center, Santa Fe Campus, Mexico City 05100, Mexico.
Manuel Colome-HidalgoInstituto de Investigación en Salud, Universidad Autònoma de Santo Domingo, Santo Domingo 10014, Dominican Republic.
Renat NurmukhametovDepartment of Neurosurgery, RUDN University, 121359 Moscow, Russia.
José Rafael Cerda CéspedesDepartamento de Farmacia Galénica, Universidad Complutense de Madrid (UCM), 28040 Madrid, Spain.
Nicola MontemurroDepartment of Neurosurgery, Azienda Ospedaliera Universitaria Pisana (AOUP), University of Pisa, 56100 Pisa, Italy.ORCID 0000-0002-3686-8907

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSimulation-based techniques using three-dimensional models are gaining popularity in neurosurgical training. Most pre-existing models are expensive, so we felt a need to develop a real-life model using 3D printing technology to train in endoscopic third ventriculostomy.

methodsThe brain model was made using a 3D-printed resin mold from patient-specific MRI data. The mold was filled with silicone Ecoflex™ 00-10 and mixed with Silc Pig

resultsSeven residents and eight senior neurosurgeons were recruited to test our model. The participants reported that the size and anatomy of the elements were very similar to real structures. The model was helpful for training neuroendoscopic 3D perception and navigation.

conclusionsWe developed an endoscopic third ventriculostomy training model using 3D printing technology that provides anatomical precision and a realistic simulation. We hope our model can provide an indispensable tool for young neurosurgeons to gain operative experience without exposing patients to risk.

Indexed as

3D printingendoscopic third ventriculostomyETVneurosurgerysimulationvirtual reality

Identifiers

PMID36830866
PMCPMC9953411

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.