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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

Patient-Specific Coronary Artery 3D Printing Based on Intravascular Optical Coherence Tomography and Coronary Angiography

Huang, Chenxi, Lan, Yisha, Chen, Sirui, Liu, Qing, Luo, Xin, Xu, Gaowei, Zhou, Wen, Lin, Fan, Peng, Yonghong, Ng, Eddie Y. K., Cheng, Yongqiang, Zeng, Nianyin, Zhang, Guokai and Che, Wenliang (2019) Patient-Specific Coronary Artery 3D Printing Based on Intravascular Optical Coherence Tomography and Coronary Angiography. Complexity, 2019 (571259). pp. 1-10. ISSN 1076-2787

Item Type: Article

Abstract

Despite the new ideas were inspired in medical treatment by the rapid advancement of three-dimensional (3D) printing technology, there is still rare research work reported on 3D printing of coronary arteries being documented in the literature. In this work, the application value of 3D printing technology in the treatment of cardiovascular diseases has been explored via comparison study between the 3D printed vascular solid model and the computer aided design (CAD) model. In this paper, a new framework is proposed to achieve a 3D printing vascular model with high simulation. The patient-specific 3D reconstruction of the coronary arteries is performed by the detailed morphological information abstracted from the contour of the vessel lumen. In the process of reconstruction which has 5 steps, the morphological details of the contour view of the vessel lumen are merged along with the curvature and length information provided by the coronary angiography. After comparing with the diameter of the narrow section and the diameter of the normal section in CAD models and 3D printing model, it can be concluded that there is a high correlation between the diameter of vascular stenosis measured in 3D printing models and computer aided design models. The 3D printing model has high-modeling ability and high precision, which can represent the original coronary artery appearance accurately. It can be adapted for prevascularization planning to support doctors in determining the surgical procedures.

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More Information

Depositing User: Leah Maughan

Identifiers

Item ID: 11518
Identification Number: https://doi.org/10.1155/2019/5712594
ISSN: 1076-2787
URI: http://sure.sunderland.ac.uk/id/eprint/11518
Official URL: http://dx.doi.org/10.1155/2019/5712594

Users with ORCIDS

ORCID for Yonghong Peng: ORCID iD orcid.org/0000-0002-5508-1819

Catalogue record

Date Deposited: 10 Feb 2020 11:47
Last Modified: 30 Sep 2020 11:16

Contributors

Author: Yonghong Peng ORCID iD
Author: Chenxi Huang
Author: Yisha Lan
Author: Sirui Chen
Author: Qing Liu
Author: Xin Luo
Author: Gaowei Xu
Author: Wen Zhou
Author: Fan Lin
Author: Eddie Y. K. Ng
Author: Yongqiang Cheng
Author: Nianyin Zeng
Author: Guokai Zhang
Author: Wenliang Che

University Divisions

Faculty of Technology > School of Computer Science

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