Mechanical metrics may show improved ability to predict osteoarthritis compared to T1rho mapping.

Journal Article (Journal Article)

Changes in cartilage structure and composition are commonly observed during the progression of osteoarthritis (OA). Importantly, quantitative magnetic resonance imaging (MRI) methods, such as T1rho relaxation imaging, can noninvasively provide in vivo metrics that reflect changes in cartilage composition and therefore have the potential for use in early OA detection. Changes in cartilage mechanical properties are also hallmarks of OA cartilage; thus, measurement of cartilage mechanical properties may also be beneficial for earlier OA detection. However, the relative predictive ability of compositional versus mechanical properties in detecting OA has yet to be determined. Therefore, we developed logistic regression models predicting OA status in an ex vivo environment using several mechanical and compositional metrics to assess which metrics most effectively predict OA status. Specifically, in this study the compositional metric analyzed was the T1rho relaxation time, while the mechanical metrics analyzed were the stiffness and recovery (defined as a measure of how quickly cartilage returns to its original shape after loading) of the cartilage. Cartilage recovery had the best predictive ability of OA status both alone and in a multivariate model including the T1rho relaxation time. These findings highlight the potential of cartilage recovery as a non-invasive marker of in vivo cartilage health and motivate future investigation of this metric clinically.

Full Text

Duke Authors

Cited Authors

  • Cutcliffe, HC; Kottamasu, PK; McNulty, AL; Goode, AP; Spritzer, CE; DeFrate, LE

Published Date

  • December 2, 2021

Published In

Volume / Issue

  • 129 /

Start / End Page

  • 110771 -

PubMed ID

  • 34627074

Pubmed Central ID

  • PMC8744537

Electronic International Standard Serial Number (EISSN)

  • 1873-2380

Digital Object Identifier (DOI)

  • 10.1016/j.jbiomech.2021.110771


  • eng

Conference Location

  • United States