title: Trabecular morphometry by fractal signature analysis is a novel marker of osteoarthritis progression.
abstract: OBJECTIVE
  To evaluate the effectiveness of using subchondral bone texture observed on a radiograph taken at baseline to predict progression of knee osteoarthritis (OA) over a 3-year period.
  
  
  METHODS
  A total of 138 participants in the Prediction of Osteoarthritis Progression study were evaluated at baseline and after 3 years. Fractal signature analysis (FSA) of the medial subchondral tibial plateau was performed on fixed flexion radiographs of 248 nonreplaced knees, using a commercially available software tool. OA progression was defined as a change in joint space narrowing (JSN) or osteophyte formation of 1 grade according to a standardized knee atlas. Statistical analysis of fractal signatures was performed using a new model based on correlating the overall shape of a fractal dimension curve with radius.
  
  
  RESULTS
  Fractal signature of the medial tibial plateau at baseline was predictive of medial knee JSN progression (area under the curve [AUC] 0.75, of a receiver operating characteristic curve) but was not predictive of osteophyte formation or progression of JSN in the lateral compartment. Traditional covariates (age, sex, body mass index, knee pain), general bone mineral content, and joint space width at baseline were no more effective than random variables for predicting OA progression (AUC 0.52-0.58). The predictive model with maximum effectiveness combined fractal signature at baseline, knee alignment, traditional covariates, and bone mineral content (AUC 0.79).
  
  
  CONCLUSIONS
  We identified a prognostic marker of OA that is readily extracted from a plain radiograph using FSA. Although the method needs to be validated in a second cohort, our results indicate that the global shape approach to analyzing these data is a potentially efficient means of identifying individuals at risk of knee OA progression.
authors: Duke University Medical Center, Durham, North Carolina 27710, USA. vbk@acpub.duke.edu
authors: Virginia Byers
authors: VB
authors: Kraus
authors: Sheng
authors: S
authors: Feng
authors: ShengChu
authors: S
authors: Wang
authors: Scott
authors: S
authors: White
authors: Maureen
authors: M
authors: Ainslie
authors: Alan
authors: A
authors: Brett
authors: Anthony
authors: A
authors: Holmes
authors: H Cecil
authors: HC
authors: Charles
mesh_terms: D000367:Age Factors; D018450:Disease Progression; D005260:Female; D017709:Fractals; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007719:Knee Joint / Q000473:pathology* / Q000503:physiopathology; D008297:Male; D020370:Osteoarthritis, Knee / Q000000981:diagnostic imaging* / Q000473:pathology / Q000503:physiopathology; D054850:Osteophyte / Q000473:pathology; D011237:Predictive Value of Tests; D012372:ROC Curve; D011859:Radiography; D013977:Tibia / Q000000981:diagnostic imaging* / Q000473:pathology / Q000503:physiopathology