Magnetic Resonance Imaging–based biomechanical simulation of cartilage: A systematic review. (February 2022)

• Record Type: Journal Article
• Authors: Seyedpour, S.M.; Nafisi, S.; Nabati, M.; Pierce, D.M.; Reichenbach, J.R.; Ricken, T.
• Is Part Of: Journal of the mechanical behavior of biomedical materials. Volume 126(2022)
• Publication Date: 2022-02
• Subjects: Biomechanics -- Cartilage -- Clinical application -- Constitutive model -- Magnetic Resonance Imaging (MRI) -- Osteoarthritis; Biomedical materials -- Periodicals; Biomedical materials -- Mechanical properties -- Periodicals; Biomedical materials; Biomedical materials -- Mechanical properties; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.jmbbm.2021.104963
• Languages: English
• ISSNs: 1751-6161

Abstract

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.