SPP2311

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In-stent restenosis in coronary arteries – computational and data-driven investigations towards translational modeling

PIs: Marek Behr, Kevin Linka, Felix Vogt

3-D reconstruction of a stented coronary artery from post-mortem µCT imaging (CARD): blue – stent; green – lumen; brown – calcification.

Aim:

The project develops computational tools for coronary stenting with drug elution to prevent in-stent restenosis. It combines medical data, cellular modeling, and blood flow dynamics to create a rapid, patient-specific simulation tool using techniques like model order reduction and neural networks.

Graphical abstract of coronary stent project project

Description:

The project aims to develop computational and data-driven techniques for coronary stenting with drug elution to prevent the development of in-stent restenosis (ISR), a disease caused by pathological tissue growth. The aim is to create an in-silico simulation tool to help cardiologists make rapid, patient-specific treatment decisions. The project involves a multidisciplinary team: Prof. Vogt provides medical data and knowledge on ISR, Prof. Linka models cellular processes, and Prof. Behr focuses on the dynamics of blood flow. Using techniques such as model order reduction and neural networks, they aim to develop a meta-model that predicts ISR outcomes based on patient-specific data.

Involved Institutions:

Chair for Computational Analysis of Technical Systems, RWTH Aachen University

Department of Internal Medicine I – Cardiology, Angiology and Intensive Care Medicine, Uniklinik RWTH Aachen

Institute for Continuum and Material Mechanics, Hamburg University of Technology

Institute of Applied Mechanics, RWTH Aachen University

Applicants:

Prof. Marek Behr, Ph.D.

Prof. Marek Behr, Ph.D.

Chair for Computational Analysis of Technical Systems, RWTH Aachen University
Dr.-Ing. Kevin Linka

Dr.-Ing. Kevin Linka

Hamburg University of Technology, Institute for Continuum and Material Mechanics
Prof. Dr. med. Felix Vogt

Prof. Dr. med. Felix Vogt

Department of Internal Medicine I - Cardiology, Angiology and Intensive Care Medicine, Uniklinik RWTH Aachen
Anna M. Ranno

Anna M. Ranno

Chair for Computational Analysis of Technical Systems, RWTH Aachen University
Mahmoud Sesa

Mahmoud Sesa

Institute of Applied Mechanics, RWTH Aachen University

Publications

2024

Ranno, A.; Manjunatha, K.; Glitz, A.; Schaaps, N.; Reese, S.; Vogt, F.; Behr, M.

In-silico Analysis of Hemodynamic Indicators in Idealized Stented Coronary Arteries for Varying Stent Indentation Unveröffentlicht

2024.

Abstract | Links | BibTeX

Shi, Jianye; Manjunatha, Kiran; Behr, Marek; Vogt, Felix; Reese, Stefanie

A physics-informed deep learning framework for modeling of coronary in-stent restenosis Artikel

In: Biomechanics and Modeling in Mechanobiology, Bd. 23, Nr. 2, S. 615–629, 2024.

BibTeX

Shi, Jianye; Manjunatha, Kiran; Vogt, Felix; Reese, Stefanie

Data-driven reduced order surrogate modeling for coronary in-stent restenosis Artikel

In: Computer Methods and Programs in Biomedicine, S. 108466, 2024.

BibTeX

2023

Manjunatha, K.; Schaaps, N.; Behr, M.; Vogt, F.; Reese, S.

Computational Modeling of In-Stent Restenosis: Pharmacokinetic and Pharmacodynamic Evaluation Artikel

In: Computers in Biology and Medicine, Ausg. 167, 2023.

Abstract | Links | BibTeX

Cornelissen, A.; Florescu, R. A.; Reese, S.; Behr, M.; Ranno, A.; Manjunatha, K.; Schaaps, N.; Böhm, C.; Liehn, E. A.; Zhao, L.; Nilcham, P.; Milzi, A.; Schröder, J.; Vogt, F. J.

In-Vivo Assessment of Vascular Injury for the Prediction of In-Stent Restenosis Artikel

In: International Journal of Cardiology, Ausg. 388, 2023.

Abstract | Links | BibTeX

Manjunatha, Kiran; Ranno, Anna; Shi, Jianye; Schaaps, Nicole; Nilcham, Pakhwan; Cornelissen, Anne; Vogt, Felix; Behr, Marek; Reese, Stefanie

A continuum chemo-mechano-biological model for in-stent restenosis with consideration of hemodynamic effects Artikel

In: GAMM-Mitteilungen, Bd. n/a, Nr. n/a, S. e202370008, 2023.

Links | BibTeX

2022

Manjunatha, K.; Behr, M.; Vogt, F.; Reese, S.

A Multiphysics Modeling Approach for In-Stent Restenosis: Theoretical Aspects and Finite Element Implementation Artikel

In: Computers in Biology and Medicine, Bd. 150, 2022.

Abstract | Links | BibTeX

Manjunatha, K.; Behr, M.; Vogt, F.; Reese, S.

Finite Element Modeling of In-Stent Restenosis Buchabschnitt

In: Link, Springer (Hrsg.): S. 305–318, 2022.

Abstract | Links | BibTeX

2020

Haßler, S.; Ranno, A.; Behr, M.

Finite-Element Formulation for Advection–Reaction Equations with Change of Variable and Discontinuity Capturing Artikel

In: CMAME, Ausg. 369, 2020.

Abstract | Links | BibTeX