title: Fully automated system for the quantification of human osteoarthritic knee joint effusion volume using magnetic resonance imaging.
abstract: BACKGROUND
  Joint effusion is frequently associated with osteoarthritis (OA) flare-up and is an important marker of therapeutic response. This study aimed at developing and validating a fully automated system based on magnetic resonance imaging (MRI) for the quantification of joint effusion volume in knee OA patients.
  
  
  METHODS
  MRI examinations consisted of two axial sequences: a T2-weighted true fast imaging with steady-state precession and a T1-weighted gradient echo. An automated joint effusion volume quantification system using MRI was developed and validated (a) with calibrated phantoms (cylinder and sphere) and effusion from knee OA patients; (b) with assessment by manual quantification; and (c) by direct aspiration. Twenty-five knee OA patients with joint effusion were included in the study.
  
  
  RESULTS
  The automated joint effusion volume quantification was developed as a four stage sequencing process: bone segmentation, filtering of unrelated structures, segmentation of joint effusion, and subvoxel volume calculation. Validation experiments revealed excellent coefficients of variation with the calibrated cylinder (1.4%) and sphere (0.8%) phantoms. Comparison of the OA knee joint effusion volume assessed by the developed automated system and by manual quantification was also excellent (r = 0.98; P < 0.0001), as was the comparison with direct aspiration (r = 0.88; P = 0.0008).
  
  
  CONCLUSIONS
  The newly developed fully automated MRI-based system provided precise quantification of OA knee joint effusion volume with excellent correlation with data from phantoms, a manual system, and joint aspiration. Such an automated system will be instrumental in improving the reproducibility/reliability of the evaluation of this marker in clinical application.
authors.affiliation: ArthroVision Inc, 1871 Sherbrooke Street East, Montreal, Quebec H2K 1B6, Canada. wei-li@arthrovision.biz
authors.forename: Wei
authors.initials: W
authors.lastname: Li
authors.forename: François
authors.initials: F
authors.lastname: Abram
authors.forename: Jean-Pierre
authors.initials: JP
authors.lastname: Pelletier
authors.forename: Jean-Pierre
authors.initials: JP
authors.lastname: Raynauld
authors.forename: Marc
authors.initials: M
authors.lastname: Dorais
authors.forename: Marc-André
authors.initials: MA
authors.lastname: d'Anjou
authors.forename: Johanne
authors.initials: J
authors.lastname: Martel-Pelletier
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001331:Automation; D005122:Exudates and Transudates; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007719:Knee Joint / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D020370:Osteoarthritis, Knee / Q000473:pathology*