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3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors

Overview of attention for article published in Advanced Materials Technologies, December 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#7 of 377)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
27 news outlets
blogs
4 blogs
twitter
10 tweeters
video
1 video uploader

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
111 Mendeley
Title
3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors
Published in
Advanced Materials Technologies, December 2017
DOI 10.1002/admt.201700235
Pubmed ID
Authors

Kaiyan Qiu, Zichen Zhao, Ghazaleh Haghiashtiani, Shuang-Zhuang Guo, Mingyu He, Ruitao Su, Zhijie Zhu, Didarul B. Bhuiyan, Paari Murugan, Fanben Meng, Sung Hyun Park, Chih-Chang Chu, Brenda M. Ogle, Daniel A. Saltzman, Badrinath R. Konety, Robert M. Sweet, Michael C. McAlpine

Abstract

The design and development of novel methodologies and customized materials to fabricate patient-specific 3D printed organ models with integrated sensing capabilities could yield advances in smart surgical aids for preoperative planning and rehearsal. Here, we demonstrate 3D printed prostate models with physical properties of tissue and integrated soft electronic sensors using custom-formulated polymeric inks. The models show high quantitative fidelity in static and dynamic mechanical properties, optical characteristics, and anatomical geometries to patient tissues and organs. The models offer tissue-mimicking tactile sensation and behavior and thus can be used for the prediction of organ physical behavior under deformation. The prediction results show good agreement with values obtained from simulations. The models also allow the application of surgical and diagnostic tools to their surface and inner channels. Finally, via the conformal integration of 3D printed soft electronic sensors, pressure applied to the models with surgical tools can be quantitatively measured.

Twitter Demographics

The data shown below were collected from the profiles of 10 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 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 111 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 23%
Student > Master 17 15%
Researcher 14 13%
Student > Bachelor 12 11%
Other 6 5%
Other 16 14%
Unknown 21 19%
Readers by discipline Count As %
Engineering 34 31%
Materials Science 15 14%
Medicine and Dentistry 11 10%
Chemistry 6 5%
Agricultural and Biological Sciences 5 5%
Other 14 13%
Unknown 26 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 215. 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 02 July 2019.
All research outputs
#85,925
of 16,116,577 outputs
Outputs from Advanced Materials Technologies
#7
of 377 outputs
Outputs of similar age
#3,594
of 411,772 outputs
Outputs of similar age from Advanced Materials Technologies
#2
of 17 outputs
Altmetric has tracked 16,116,577 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 377 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.7. This one has done particularly well, scoring higher than 98% of its peers.
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 411,772 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.