The feasibility of characterizing the spatial distribution of cartilage T(2) using texture analysis

Osteoarthritis Cartilage. 2008 May;16(5):584-90. doi: 10.1016/j.joca.2007.10.019. Epub 2008 Mar 11.

Abstract

Objective: The purpose of this study was (1) to characterize the spatial distribution of cartilage T(2) in postmenopausal osteoarthritis (OA) patients and age-matched healthy subjects using second order texture measures at baseline, and (2) to analyze changes in the texture of cartilage T(2) after 9 months.

Methods: 3.0T-MRI of the knee was performed in 8 mild OA patients and 10 age-matched controls at baseline and after 9 months. Cartilage T(2), volume, and average thickness were calculated in all patients. Texture analysis, based on the gray level co-occurrence matrix, was performed on the cartilage T(2) maps. Texture parameters, including entropy and angular second moment, were calculated at 0 degrees (corresponding to the anterior-posterior axis) and at 90 degrees (corresponding to the superior-inferior axis), with pixel offsets ranging from 1 to 3 pixels.

Results: Least square means analysis showed that mean T(2) values, their standard deviation (SD), and their entropy were greater (P<0.05) in OA patients than in controls. Over 9 months, the SD and entropy of cartilage T(2) significantly (P<0.05) decreased in OA patients, while no significant changes were evident in cartilage thickness or volume.

Conclusion: The mean cartilage T(2) values, their SD, and their entropy were greater in OA patients than in controls, indicating that the T(2) values in osteoarthritic cartilage are not only elevated, but also more heterogeneous than those in healthy cartilage. The longitudinal results demonstrate that changes in texture parameters of cartilage T(2) may precede morphological changes in thickness and volume in the progression of OA.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cartilage, Articular / pathology*
  • Entropy
  • Epidemiologic Methods
  • Female
  • Humans
  • Image Interpretation, Computer-Assisted / methods
  • Magnetic Resonance Imaging / methods
  • Middle Aged
  • Osteoarthritis, Knee / pathology*
  • Postmenopause