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3D printed ventricular septal defect patch: a primer for the 2015 Radiological Society of North America (RSNA) hands-on course in 3D printing

Overview of attention for article published in 3D Printing in Medicine, November 2015
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2 tweeters

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28 Dimensions

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55 Mendeley
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Title
3D printed ventricular septal defect patch: a primer for the 2015 Radiological Society of North America (RSNA) hands-on course in 3D printing
Published in
3D Printing in Medicine, November 2015
DOI 10.1186/s41205-015-0002-4
Pubmed ID
Authors

Andreas A. Giannopoulos, Leonid Chepelev, Adnan Sheikh, Aili Wang, Wilfred Dang, Ekin Akyuz, Chris Hong, Nicole Wake, Todd Pietila, Philip B. Dydynski, Dimitrios Mitsouras, Frank J. Rybicki

Abstract

Hand-held three dimensional models of the human anatomy and pathology, tailored-made protheses, and custom-designed implants can be derived from imaging modalities, most commonly Computed Tomography (CT). However, standard DICOM format images cannot be 3D printed; instead, additional image post-processing is required to transform the anatomy of interest into Standard Tessellation Language (STL) format is needed. This conversion, and the subsequent 3D printing of the STL file, requires a series of steps. Initial post-processing involves the segmentation-demarcation of the desired for 3D printing parts and creating of an initial STL file. Then, Computer Aided Design (CAD) software is used, particularly for wrapping, smoothing and trimming. Devices and implants that can also be 3D printed, can be designed using this software environment. The purpose of this article is to provide a tutorial on 3D Printing with the test case of complex congenital heart disease (CHD). While the infant was born with double outlet right ventricle (DORV), this hands-on guide to be featured at the 2015 annual meeting of the Radiological Society of North America Hands-on Course in 3D Printing focused on the additional finding of a ventricular septal defect (VSD). The process of segmenting the heart chambers and the great vessels will be followed by optimization of the model using CAD software. A virtual patch that accurately matches the patient's VSD will be designed and both models will be prepared for 3D printing.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Unknown 54 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 22%
Student > Master 9 16%
Student > Bachelor 8 15%
Researcher 5 9%
Other 3 5%
Other 9 16%
Unknown 9 16%
Readers by discipline Count As %
Engineering 13 24%
Medicine and Dentistry 11 20%
Physics and Astronomy 4 7%
Materials Science 3 5%
Biochemistry, Genetics and Molecular Biology 3 5%
Other 9 16%
Unknown 12 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 January 2016.
All research outputs
#5,454,450
of 9,723,270 outputs
Outputs from 3D Printing in Medicine
#11
of 17 outputs
Outputs of similar age
#169,885
of 328,213 outputs
Outputs of similar age from 3D Printing in Medicine
#2
of 3 outputs
Altmetric has tracked 9,723,270 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 17 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one scored the same or higher as 6 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 328,213 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.