A fully coupled framework for in silico investigation of in-stent restenosis-Reference-Cited by-同舟云学术

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A fully coupled framework for in silico investigation of in-stent restenosis

Published:2018-12-31 Issue:2 Volume:22 Page:217-228
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

Li Shibo¹,Lei Long¹,Hu Ying¹,Zhang Yanfang²,Zhao Shijia¹,Zhang Jianwei³

Affiliation:

1. Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China;

2. Department of Interventional Radiology, Shenzhen People’s Hospital, Shenzhen, China;

3. TAMS, Department of Informatics, University of Hamburg, Hamburg, Germany

Funder

Shenzhen Fundamental Research Funds

Shenzhen Key Laboratory Project

Shenzhen Peacock Plan

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2018.1545017

Reference30 articles.

1. In Silico Prediction of the Mechanobiological Response of Arterial Tissue: Application to Angioplasty and Stenting

2. A Complex Automata approach for in-stent restenosis: Two-dimensional multiscale modelling and simulations

3. Simulation of avascular tumor growth by agent-based game model involving phenotype-phenotype interactions

4. Lumen diameter of normal human coronary arteries. Influence of age, sex, anatomic variation, and left ventricular hypertrophy or dilation.

5. Small stent size and intimal hyperplasia contribute to restenosis: A volumetric intravascular ultrasound analysis

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1. A quantitative study of the effects of a dual layer coating drug-eluting stent on safety and efficacy;Journal of Biomechanics;2024-11

2. Impact of Tissue Damage and Hemodynamics on Restenosis Following Percutaneous Transluminal Angioplasty: A Patient-Specific Multiscale Model;Annals of Biomedical Engineering;2024-05-03

3. A physics-informed deep learning framework for modeling of coronary in-stent restenosis;Biomechanics and Modeling in Mechanobiology;2024-01-18

4. Computational modeling of in-stent restenosis: Pharmacokinetic and pharmacodynamic evaluation;Computers in Biology and Medicine;2023-12

5. Coupling Between a Finite Element Model of Coronary Artery Mechanics and a Microscale Agent-Based Model of Smooth Muscle Cells Through Trilinear Interpolation;Computational Science – ICCS 2023;2023

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