Measurement of localized cartilage volume and thickness of human knee joints by computer analysis of three-dimensional magnetic resonance images

Invest Radiol. 1998 May;33(5):289-99. doi: 10.1097/00004424-199805000-00006.

Abstract

Rationale and objectives: This work demonstrates a new method for computerized measurement of the dimensions (thickness and volume) of articular cartilage for any specified region of the human knee joint. Three-dimensional magnetic resonance (MR) images optimized for cartilage contrast have been analyzed using computerized edge-detection techniques, and the reproducibility of articular cartilage thickness and volume measurements is assessed.

Methods: A fat-suppressed, three-dimensional SPoiled GRass MR sequence (45/7.5/30 degrees) with total scan time of approximately 12 minutes was used to acquire volume images of human knee joints at spatial resolution of 0.6 x 1.2 x 1.2 mm. Measurements were made using six repeated scans for three healthy volunteers over a period of 2 months. The subsequent semi-automated image processing to establish total cartilage volume and cartilage thickness maps for the femur required approximately 60 minutes of operator time.

Results: The mean coefficient of variation for total cartilage volume for the six repeated scans for the three volunteers was 3.8%, and the average coefficient of variation for the user-selected cartilage plugs was 2.0%. The cartilage thickness maps from the repeated scans of the same knee were similar.

Conclusions: Standard resolution MR images with fat-suppressed contrast lead to an objective and reproducible measurement of spatial dimensions of articular cartilage when analyzed semi-automatically using computerized edge-detection methods.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Cartilage, Articular / anatomy & histology*
  • Female
  • Humans
  • Image Processing, Computer-Assisted*
  • Knee Joint / anatomy & histology*
  • Magnetic Resonance Imaging / methods*
  • Male
  • Middle Aged
  • Reproducibility of Results