Evidence map›Paper›PMID 33396859›Full record

ArticlePolymers2020

Manufacturing and Characterization of Hybrid Bulk Voxelated Biomaterials Printed by Digital Anatomy 3D Printing.

Hyeonu Heo, Yuqi Jin, David Yang, Christopher Wier, Aaron Minard, Narendra B Dahotre, Arup Neogi

Abstract read
In one paragraph

Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

7 authors.

Hyeonu HeoDepartment of Physics, University of North Texas, Denton, TX 76203, USA.ORCID 0000-0003-0116-0471
Yuqi JinDepartment of Physics, University of North Texas, Denton, TX 76203, USA.ORCID 0000-0001-7798-8086
David YangStratasys, Mountain View, CA 94043, USA.
Christopher WierStratasys, Mountain View, CA 94043, USA.
Aaron MinardTechnical Laboratory Systems, Inc., Katy, TX 77494, USA.
Narendra B DahotreDepartment of Materials Science and Engineering, University of North Texas, Denton, TX 76207, USA.
Arup NeogiDepartment of Physics, University of North Texas, Denton, TX 76203, USA.ORCID 0000-0003-3075-8683

Funding

National Science Foundation 1741677
6 · The paper itself

Abstract

The advent of 3D digital printers has led to the evolution of realistic anatomical organ shaped structures that are being currently used as experimental models for rehearsing and preparing complex surgical procedures by clinicians. However, the actual material properties are still far from being ideal, which necessitates the need to develop new materials and processing techniques for the next generation of 3D printers optimized for clinical applications. Recently, the voxelated soft matter technique has been introduced to provide a much broader range of materials and a profile much more like the actual organ that can be designed and fabricated voxel by voxel with high precision. For the practical applications of 3D voxelated materials, it is crucial to develop the novel high precision material manufacturing and characterization technique to control the mechanical properties that can be difficult using the conventional methods due to the complexity and the size of the combination of materials. Here we propose the non-destructive ultrasound effective density and bulk modulus imaging to evaluate 3D voxelated materials printed by J750 Digital Anatomy 3D Printer of Stratasys. Our method provides the design map of voxelated materials and substantially broadens the applications of 3D digital printing in the clinical research area.

Indexed as

digital anatomy 3D printingnon-destructive testingultrasound elastographyvoxel

Identifiers

PMID33396859
PMCPMC7796254

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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.