title: Inter-subject comparison of MRI knee cartilage thickness.
abstract: In this paper, we present the development and application of current image processing techniques to perform MRI inter-subject comparison of knee cartilage thickness based on the registration of bone structures. Each point in the bone surface which is part of the bone-cartilage interface is assigned a cartilage thickness value. Cartilage and corresponding bone structures are segmented and their shapes interpolated to create isotropic voxels. Cartilage thicknesses are computed for each point in the bone-cartilage interfaces and transferred to the bone surfaces. Corresponding anatomic points are then computed for bone surfaces based on shape matching using 3D shape descriptors called shape contexts to register bones with affine and elastic transformations, and then perform a point to point comparison of cartilage thickness values. An alternative technique for cartilage shape interpolation using a morphing technique is also presented. The cartilage segmentation and morphing were validated visually, based on volumetric measurements of porcine knee images which cartilage volumes were measured using a water displacement method, and based on digital thickness values computed with an established technique. Shape matching using 3D shape contexts was validated visually and against manual shape matching performed by a radiologist. The reproducibility of intra- and inter-subject cartilage thickness comparisons was established, as well as the feasibility of using the proposed technique to build a mean femoral shape, cartilage thickness map, and cartilage coverage map. Results showed that the proposed technique is robust, accurate, and reproducible to perform point to point inter-subject comparison of knee cartilage thickness values.
authors.affiliation: MQIR, Department of Radiology, University of California, QB3 Building, 2nd Floor, 201, 1700 - 4th Street, San Francisco, CA 94158, USA. Julio.Carballido@radiology.ucsf.edu
authors.forename: Julio
authors.initials: J
authors.lastname: Carballido-Gamio
authors.forename: Jan S
authors.initials: JS
authors.lastname: Bauer
authors.forename: Robert
authors.initials: R
authors.lastname: Stahl
authors.forename: Keh-Yang
authors.initials: KY
authors.lastname: Lee
authors.forename: Stefanie
authors.initials: S
authors.lastname: Krause
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Link
authors.forename: Sharmila
authors.initials: S
authors.lastname: Majumdar
mesh_terms: D000465:Algorithms; D002358:Cartilage, Articular / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007719:Knee Joint / Q000033:anatomy & histology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique