Evidence map›Paper›PMID 35237891›Full record

ArticleJournal of digital imaging2022

Medical 3D Printing Dimensional Accuracy for Multi-pathological Anatomical Models 3D Printed Using Material Extrusion.

Prashanth Ravi, Leonid L Chepelev, Gabrielle V Stichweh, Benjamin S Jones, Frank J Rybicki

Open access · greenAbstract read
In one paragraph

Article in Journal of digital imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.4field-weighted citation impact, top 12% of its field
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

17 citing papers in PubMed, 32 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Prashanth RaviDepartment of Radiology, University of Cincinnati College of Medicine, 234 Goodman St, Cincinnati, OH, 45219, USA. raviph@ucmail.uc.edu.ORCID http://orcid.org/0000-0001-9938-8524
Leonid L ChepelevDepartment of Radiology, Stanford University, 300 Pasteur Dr, Stanford, CA, 94305, USA.
Gabrielle V Stichweh1819 Innovation Hub Makerspace, University of Cincinnati, 2900 Reading Rd, Cincinnati, OH, 45206, USA.
Benjamin S Jones1819 Innovation Hub Makerspace, University of Cincinnati, 2900 Reading Rd, Cincinnati, OH, 45206, USA.
Frank J RybickiDepartment of Radiology, University of Cincinnati College of Medicine, 234 Goodman St, Cincinnati, OH, 45219, USA.
University of Cincinnati · USStanford University · USUniversity of Cincinnati Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical 3D printing of anatomical models is being increasingly applied in healthcare facilities. The accuracy of such 3D-printed anatomical models is an important aspect of their overall quality control. The purpose of this research was to test whether the accuracy of a variety of anatomical models 3D printed using Material Extrusion (MEX) lies within a reasonable tolerance level, defined as less than 1-mm dimensional error. Six medical models spanning across anatomical regions (musculoskeletal, neurological, abdominal, cardiovascular) and sizes (model volumes ranging from ~ 4 to 203 cc) were chosen for the primary study. Three measurement landing blocks were strategically designed within each of the six medical models to allow high-resolution caliper measurements. An 8-cc reference cube was printed as the 7th model in the primary study. In the secondary study, the effect of model rotation and scale was assessed using two of the models from the first study. All models were 3D printed using an Ultimaker 3 printer in triplicates. All absolute measurement errors were found to be less than 1 mm with a maximum error of 0.89 mm. The maximum relative error was 2.78%. The average absolute error was 0.26 mm, and the average relative error was 0.71% in the primary study, and the results were similar in the secondary study with an average absolute error of 0.30 mm and an average relative error of 0.60%. The relative errors demonstrated certain patterns in the data, which were explained based on the mechanics of MEX 3D printing. Results indicate that the MEX process, when carefully assessed on a case-by-case basis, could be suitable for the 3D printing of multi-pathological anatomical models for surgical planning if an accuracy level of 1 mm is deemed sufficient for the application.

Indexed as

Models, AnatomicPrinting, Three-DimensionalHeartHumansAccuracyAnatomical modelsMaterial extrusionMedical 3D printingSurgical planningUltimaker 3

Identifiers

PMID35237891
PMCPMC9156585
OpenAlexW4214819520

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.