title: Scan-rescan precision of subchondral bone curvature maps from routine 3D DESS water excitation sequences: Data from the Osteoarthritis Initiative.
abstract: BACKGROUND
  Subchondral bone (SCB) undergoes changes in the shape of the articulating bone surfaces and is currently recognized as a key target in osteoarthritis (OA) treatment. The aim of this study was to present an automated system that determines the curvature of the SCB regions of the knee and to evaluate its cross-sectional and longitudinal scan-rescan precision
  
  
  METHODS
  Six subjects with OA and six control subjects were selected from the Osteoarthritis Initiative (OAI) pilot study database. As per OAI protocol, these subjects underwent 3T MRI at baseline and every twelve months thereafter, including a 3D DESS WE sequence. We analyzed the baseline and twenty-four month images. Each subject was scanned twice at these visits, thus generating scan-rescan information. Images were segmented with an automated multi-atlas framework platform and then 3D renderings of the bone structure were created from the segmentations. Curvature maps were extracted from the 3D renderings and morphed into a reference atlas to determine precision, to generate population statistics, and to visualize cross-sectional and longitudinal curvature changes.
  
  
  RESULTS
  The baseline scan-rescan root mean square error values ranged from 0.006mm(-1) to 0.013mm(-1), and from 0.007mm(-1) to 0.018mm(-1) for the SCB of the femur and the tibia, respectively. The standardized response of the mean of the longitudinal changes in curvature in these regions ranged from -0.09 to 0.02 and from -0.016 to 0.015, respectively.
  
  
  CONCLUSIONS
  The fully automated system produces accurate and precise curvature maps of femoral and tibial SCB, and will provide a valuable tool for the analysis of the curvature changes of articulating bone surfaces during the course of knee OA.
authors.affiliation: Qmetrics Technology, LLC, Rochester, NY, United States.
authors.forename: Joshua M
authors.initials: JM
authors.lastname: Farber
authors.affiliation: Qmetrics Technology, LLC, Rochester, NY, United States.
authors.forename: Saara M S
authors.initials: SM
authors.lastname: Totterman
authors.affiliation: Departamento de Investigación e Innovación, Escuela de Medicina, Tecnológico de Monterrey, Monterrey, NL, Mexico.
authors.forename: Antonio
authors.initials: A
authors.lastname: Martinez-Torteya
authors.affiliation: Qmetrics Technology, LLC, Rochester, NY, United States; Departamento de Investigación e Innovación, Escuela de Medicina, Tecnológico de Monterrey, Monterrey, NL, Mexico. Electronic address: jose.tamezpena@itesm.mx.
authors.forename: Jose G
authors.initials: JG
authors.lastname: Tamez-Peña
mesh_terms: D016208:Databases, Factual; D005260:Female; D005269:Femur / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D020370:Osteoarthritis, Knee / Q000000981:diagnostic imaging*; D011859:Radiography; D013977:Tibia / Q000000981:diagnostic imaging*
keywords: Automated bone segmentation; Biomedical image processing; Magnetic resonance imaging; Osteoarthritis; Three-dimensional rendering curvature analysis