Evidence map›Paper›PMID 26042609›Full record

ArticleScientific reports2015

Three-dimensional virtual surgery models for percutaneous coronary intervention (PCI) optimization strategies.

Hujun Wang, Jinghua Liu, Xu Zheng, Xiaohui Rong, Xuwei Zheng, Hongyu Peng, Zhanghua Silber-Li, Mujun Li, Liyu Liu

Abstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

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  15. 3D printing in medicine: current applications and future directions.Quantitative imaging in medicine and surgery · 2018
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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

9 authors.

Hujun WangDepartment of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
Jinghua LiuDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Disease, Beijing 100029, China.
Xu ZhengState key laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China.
Xiaohui RongKey Laboratory of Soft Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China.
Xuwei ZhengDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Disease, Beijing 100029, China.
Hongyu PengDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Disease, Beijing 100029, China.
Zhanghua Silber-LiState key laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China.
Mujun LiDepartment of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China.
Liyu LiuKey Laboratory of Soft Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Percutaneous coronary intervention (PCI), especially coronary stent implantation, has been shown to be an effective treatment for coronary artery disease. However, in-stent restenosis is one of the longstanding unsolvable problems following PCI. Although stents implanted inside narrowed vessels recover normal flux of blood flows, they instantaneously change the wall shear stress (WSS) distribution on the vessel surface. Improper stent implantation positions bring high possibilities of restenosis as it enlarges the low WSS regions and subsequently stimulates more epithelial cell outgrowth on vessel walls. To optimize the stent position for lowering the risk of restenosis, we successfully established a digital three-dimensional (3-D) model based on a real clinical coronary artery and analysed the optimal stenting strategies by computational simulation. Via microfabrication and 3-D printing technology, the digital model was also converted into in vitro microfluidic models with 3-D micro channels. Simultaneously, physicians placed real stents inside them; i.e., they performed "virtual surgeries". The hydrodynamic experimental results showed that the microfluidic models highly inosculated the simulations. Therefore, our study not only demonstrated that the half-cross stenting strategy could maximally reduce restenosis risks but also indicated that 3-D printing combined with clinical image reconstruction is a promising method for future angiocardiopathy research.

Indexed as

Models, CardiovascularPrinting, Three-DimensionalComputer SimulationCoronary AngiographyCoronary Artery DiseaseCoronary RestenosisHemodynamicsHumansMicrofluidicsPercutaneous Coronary InterventionStents

Identifiers

PMID26042609
PMCPMC4455241

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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.