title: Automatic measurement and visualization of focal femoral cartilage thickness in stress-based regions of interest using three-dimensional knee models.
abstract: OBJECTIVE
  Thinning of cartilage is a common manifestation of osteoarthritis. This study addresses the need of measuring the focal femoral cartilage thickness at the weight- bearing regions of the knee by developing a reproducible and automatic method from MR images.
  
  
  METHODS
  3D models derived from semiautomatic MR image segmentations were used in this study. Two different methods were examined for identifying the mechanical loading of the knee articulation. The first was based on a generic weight-bearing regions definition, derived from gait characteristics and cadaver studies. The second used a physically based simulation to identify the patient-specific stress distribution of the femoral cartilage, taking into account the forces and movements of the knee. For this purpose, four different scenarios were defined in our 3D finite element (FE) simulations. The radial method was used to calculate the cartilage thickness in stress-based regions of interest, and a study was performed to validate the accuracy and suitability of the radial thickness measurements.
  
  
  RESULTS
  Detailed focal maps using our simulation data and regional measurements of cartilage thickness are given. We present the outcome of the different simulation scenarios and discuss how the internal/external rotations of the knee alter the overall stress distribution and affect the shape and size of the calculated weight-bearing areas. The use of FE simulations allows for a patient-specific calculation of the focal cartilage thickness.
  
  
  CONCLUSIONS
  It is important to assess the quantification of focal knee cartilage morphology to monitor the progression of joint diseases or related treatments. When this assessment is based on MR images, accurate and robust tools are required. In this paper, we presented a set of techniques and methodologies in order to accomplish this goal and move toward personalized medicine.
authors.affiliation: Sosteco Sismat S.r.l., Genoa, Italy. marios.pitikakis@gmail.com.
authors.forename: Marios
authors.initials: M
authors.lastname: Pitikakis
authors.affiliation: MIRALab, University of Geneva, Geneva, Switzerland.
authors.forename: Andra
authors.initials: A
authors.lastname: Chincisan
authors.affiliation: MIRALab, University of Geneva, Geneva, Switzerland.
authors.forename: Nadia
authors.initials: N
authors.lastname: Magnenat-Thalmann
authors.affiliation: Sosteco Sismat S.r.l., Genoa, Italy.
authors.forename: Lorenzo
authors.initials: L
authors.lastname: Cesario
authors.affiliation: Sosteco Sismat S.r.l., Genoa, Italy.
authors.forename: Patrizia
authors.initials: P
authors.lastname: Parascandolo
authors.affiliation: Sosteco Sismat S.r.l., Genoa, Italy.
authors.forename: Loris
authors.initials: L
authors.lastname: Vosilla
authors.affiliation: Sosteco Sismat S.r.l., Genoa, Italy.
authors.forename: Gianni
authors.initials: G
authors.lastname: Viano
mesh_terms: D000328:Adult; D002358:Cartilage, Articular / Q000000981:diagnostic imaging* / Q000473:pathology; D005269:Femur / Q000000981:diagnostic imaging*; D006801:Humans; D007719:Knee Joint / Q000000981:diagnostic imaging*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D009929:Organ Size; D020370:Osteoarthritis, Knee / Q000000981:diagnostic imaging; D055815:Young Adult
keywords: 3D models; Cartilage thickness; Computer-aided diagnosis; Knee; MRI; Stress simulation; Weight-bearing areas