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Quantitative MRI methods for the assessment of structure, composition, and function of musculoskeletal tissues in basic research and preclinical applications. | LitMetric

AI Article Synopsis

  • * Quantitative MRI (qMRI) goes beyond traditional anatomical MRI by measuring tissue properties at the molecular level, helping to characterize structural integrity, biochemical content, and mechanical properties of musculoskeletal tissues.
  • * The article reviews qMRI techniques, focusing on articular cartilage, discussing their mechanisms, limitations, and potential for early OA detection and treatment evaluation, while also exploring the role of advanced technologies like machine learning in OA research.

Article Abstract

Osteoarthritis (OA) is a disabling chronic disease involving the gradual degradation of joint structures causing pain and dysfunction. Magnetic resonance imaging (MRI) has been widely used as a non-invasive tool for assessing OA-related changes. While anatomical MRI is limited to the morphological assessment of the joint structures, quantitative MRI (qMRI) allows for the measurement of biophysical properties of the tissues at the molecular level. Quantitative MRI techniques have been employed to characterize tissues' structural integrity, biochemical content, and mechanical properties. Their applications extend to studying degenerative alterations, early OA detection, and evaluating therapeutic intervention. This article is a review of qMRI techniques for musculoskeletal tissue evaluation, with a particular emphasis on articular cartilage. The goal is to describe the underlying mechanism and primary limitations of the qMRI parameters, their association with the tissue physiological properties and their potential in detecting tissue degeneration leading to the development of OA with a primary focus on basic and preclinical research studies. Additionally, the review highlights some clinical applications of qMRI, discussing the role of texture-based radiomics and machine learning in advancing OA research.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11582218PMC
http://dx.doi.org/10.1007/s10334-024-01174-7DOI Listing

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