Evidence map›Paper›PMID 34683649›Full record

ArticleMaterials (Basel, Switzerland)2021

Additive Manufacturing for Neurosurgery: Digital Light Processing of Individualized Patient-Specific Cerebral Aneurysms.

Stefano Guarino, Enrico Marchese, Gennaro Salvatore Ponticelli, Alba Scerrati, Vincenzo Tagliaferri, Federica Trovalusci

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

Stefano GuarinoDepartment of Engineering, University of Rome "Niccolò Cusano", Via Don Carlo Gnocchi 3, 00166 Rome, Italy.ORCID 0000-0001-5474-0440
Enrico MarcheseDepartment of Neurosurgery, Catholic University of Rome, L.go A. Gemelli 8, 00100 Rome, Italy.
Gennaro Salvatore PonticelliDepartment of Engineering, University of Rome "Niccolò Cusano", Via Don Carlo Gnocchi 3, 00166 Rome, Italy.ORCID 0000-0001-7984-4334
Alba ScerratiDepartment of Transalational Medicine, University of Ferrara, Via Aldo Moro 8, 44124 Ferrara, Italy.
Vincenzo TagliaferriDepartment of Enterprise Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy.ORCID 0000-0003-3609-622X
Federica TrovalusciDepartment of Enterprise Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims at demonstrating the feasibility of reproducing individualized patient-specific three-dimensional models of cerebral aneurysms by using the direct light processing (DLP) 3D printing technique in a low-time and inexpensive way. Such models were used to help neurosurgeons understand the anatomy of the aneurysms together with the surrounding vessels and their relationships, providing, therefore, a tangible supporting tool with which to train and plan surgical operations. The starting 3D models were obtained by processing the computed tomography angiographies and the digital subtraction angiographies of three patients. Then, a 3D DLP printer was used to print the models, and, if acceptable, on the basis of the neurosurgeon's opinion, they were used for the planning of the neurosurgery operation and patient information. All the models were printed within three hours, providing a comprehensive representation of the cerebral aneurysms and the surrounding structures and improving the understanding of their anatomy and simplifying the planning of the surgical operation.

Indexed as

3D printingadditive manufacturingcerebral aneurysmsdigital light processingneurosurgery

Identifiers

PMID34683649
PMCPMC8539393

What OpenQuestion holds

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Registered trials

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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.