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Seyedpour SM, Nafisi S, Nabati M, Pierce DM, Reichenbach JR, Ricken T. Magnetic Resonance Imaging-based biomechanical simulation of cartilage: A systematic review. J Mech Behav Biomed Mater 2021; 126:104963. [PMID: 34894500 DOI: 10.1016/j.jmbbm.2021.104963] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Revised: 10/30/2021] [Accepted: 11/06/2021] [Indexed: 11/19/2022]
Abstract
MRI-based mathematical and computational modeling studies can contribute to a better understanding of the mechanisms governing cartilage's mechanical performance and cartilage disease. In addition, distinct modeling of cartilage is needed to optimize artificial cartilage production. These studies have opened up the prospect of further deepening our understanding of cartilage function. Furthermore, these studies reveal the initiation of an engineering-level approach to how cartilage disease affects material properties and cartilage function. Aimed at researchers in the field of MRI-based cartilage simulation, research articles pertinent to MRI-based cartilage modeling were identified, reviewed, and summarized systematically. Various MRI applications for cartilage modeling are highlighted, and the limitations of different constitutive models used are addressed. In addition, the clinical application of simulations and studied diseases are discussed. The paper's quality, based on the developed questionnaire, was assessed, and out of 79 reviewed papers, 34 papers were determined as high-quality. Due to the lack of the best constitutive models for various clinical conditions, researchers may consider the effect of constitutive material models on the cartilage disease simulation. In the future, research groups may incorporate various aspects of machine learning into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification, such as gait analysis.
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Affiliation(s)
- S M Seyedpour
- Institute of Mechanics, Structural Analysis and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Pfaffenwaldring 27, 70569 Stuttgart, Germany; Biomechanics Lab, Institute of Mechanics, Structural Analysis and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Pfaffenwaldring 27, 70569 Stuttgart, Germany
| | - S Nafisi
- Faculty of Pharmacy, Istinye University, Maltepe, Cirpici Yolu B Ck. No. 9, 34010 Zeytinburnu, Istanbul, Turkey
| | - M Nabati
- Department of Mechanical Engineering, Faculty of Engineering, Boğaziçi University, 34342 Bebek, Istanbul, Turkey
| | - D M Pierce
- Department of Mechanical Engineering, University of Connecticut, 191 Auditorium Road, Unit 3139, Storrs, CT, 06269, USA; Department of Biomedical Engineering, University of Connecticut, 260 Glenbrook Road, Unit 3247, Storrs, CT, 06269, USA
| | - J R Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital-Friedrich Schiller University Jena, Jena, Germany; Center of Medical Optics and Photonics, Friedrich Schiller University Jena, Germany; Michael Stifel Center for Data-driven and Simulation Science Jena, Friedrich Schiller University Jena, Germany
| | - T Ricken
- Institute of Mechanics, Structural Analysis and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Pfaffenwaldring 27, 70569 Stuttgart, Germany; Biomechanics Lab, Institute of Mechanics, Structural Analysis and Dynamics, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart, Pfaffenwaldring 27, 70569 Stuttgart, Germany.
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