title: Local area cartilage segmentation: a semiautomated novel method of measuring cartilage loss in knee osteoarthritis.
abstract: OBJECTIVE
  To assess the responsiveness and reader time of a novel semiautomated tool to detect knee cartilage loss over 2 years in subjects with knee osteoarthritis.
  
  
  METHODS
  A total of 122 subjects from the Osteoarthritis Initiative progression cohort were selected. A reader used the software method to segment cartilage on double-echo steady-state sequence scans in the medial compartment of the femur from the baseline and 24-month visits. Change in cartilage volume (ΔV) was measured at a fixed weight-bearing (WB) location with respect to the 3-dimensional coordinate system based on cylindrical coordinates. Change was measured for 5 regions of varying WB surface area centered on the fixed point. The average change (ΔV), the SD of ΔV, and the standardized response mean (SRM) are reported.
  
  
  RESULTS
  The SRM was −0.52 for the largest region and decreased in magnitude as smaller regions of cartilage were probed. The average evaluation time was <20 minutes per knee compartment, split approximately evenly between a technician and a trained reader.
  
  
  CONCLUSIONS
  The results establish that measurement of cartilage loss in a local region can be done efficiently and that the resultant measures are responsive to loss of cartilage over time. The coordinate system can potentially be used to objectively examine and establish a consistent location for all knees that is most responsive to change in cartilage volume. This technique can provide rapidly an objective quantitative measure of cartilage loss and could substantially reduce study costs for large trials and data sets.
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Duryea
authors.forename: Tannaz
authors.initials: T
authors.lastname: Iranpour-Boroujeni
authors.forename: Jamie E
authors.initials: JE
authors.lastname: Collins
authors.forename: Case
authors.initials: C
authors.lastname: Vanwynngaarden
authors.forename: Ali
authors.initials: A
authors.lastname: Guermazi
authors.forename: Jeffrey N
authors.initials: JN
authors.lastname: Katz
authors.forename: Elena
authors.initials: E
authors.lastname: Losina
authors.forename: Ruby
authors.initials: R
authors.lastname: Russell
authors.forename: Charles
authors.initials: C
authors.lastname: Ratzlaff
mesh_terms: D000368:Aged; D001331:Automation; D002356:Cartilage / Q000473:pathology*; D018450:Disease Progression; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007719:Knee Joint / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D020370:Osteoarthritis, Knee / Q000473:pathology*; D011237:Predictive Value of Tests; D012720:Severity of Illness Index; D012984:Software; D013997:Time Factors